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10. The computer-implemented method of claim 3 , further comprising: inputting the plurality of decorated queries into a custom Stemmer; and stripping off the decorations of each of the plurality of decorated queries by removing each suffix to obtain stripped queries; and storing each suffix associated with each of the plurality of decorated queries for future appending.

10. The computer-implemented method of claim 3 , further comprising: inputting the plurality of decorated queries into a custom Stemmer; and stripping off the decorations of each of the plurality of decorated queries by removing each suffix to obtain stripped queries; and storing each suffix associated with each of the plurality of decorated queries for future appending. 15. The computer-implemented method of claim 10 , further comprising: inputting the stripped queries into an original Stemmer of the full-text search engine; obtaining from the original Stemmer variations of each of the stripped queries to obtain query variations; inputting the stripped queries and the query variations into the custom Stemmer; appending the removed suffixes to their proper stripped queries and the query variations to obtain an expanded set of decorated queries; and searching the full-text index using the expanded set of decorated queries.

14. An apparatus comprising: a network interface unit configured to enable communications over a network; a memory; a processor coupled to the network interface unit and the memory, the processor configured to: receive a trigger for an operation command to be executed on one or more network devices in the network; establish a connection to one or more network devices in the network; generate a command line interface command for execution of the operation command by one or more network devices, a randomly generated string being included at the end of the command line interface command; send the command line interface command over the network in order to invoke the operation command on one or more network devices on the network; receive output of the operation command from one or more devices; detect an end of the operation command output based on the randomly generated string; and parse the operation command output generated by the device using an XML based parser.

14. An apparatus comprising: a network interface unit configured to enable communications over a network; a memory; a processor coupled to the network interface unit and the memory, the processor configured to: receive a trigger for an operation command to be executed on one or more network devices in the network; establish a connection to one or more network devices in the network; generate a command line interface command for execution of the operation command by one or more network devices, a randomly generated string being included at the end of the command line interface command; send the command line interface command over the network in order to invoke the operation command on one or more network devices on the network; receive output of the operation command from one or more devices; detect an end of the operation command output based on the randomly generated string; and parse the operation command output generated by the device using an XML based parser. 20. The apparatus of claim 14 , wherein the operation command is a configuration command for configuring a function or attribute of a function of the one or more network devices.

1. A computer-implemented method for automatically providing speech synthesis, the method comprising: receiving a text string; determining whether a rendered audio file of the text string exists; if the rendered audio file does not exist, creating an audio file rendering of the text string, wherein the audio file is stored for retrieval upon subsequent receipt of the text string; and generating, by a processor, a unique identifier derived from the received text string according to a hash function, wherein the stored rendered audio file is identified based on the unique identifier that includes a hash index.

1. A computer-implemented method for automatically providing speech synthesis, the method comprising: receiving a text string; determining whether a rendered audio file of the text string exists; if the rendered audio file does not exist, creating an audio file rendering of the text string, wherein the audio file is stored for retrieval upon subsequent receipt of the text string; and generating, by a processor, a unique identifier derived from the received text string according to a hash function, wherein the stored rendered audio file is identified based on the unique identifier that includes a hash index. 6. A computer-implemented method according to claim 1 , the method further comprising: generating a reference to the rendered audio file for access via a web-based interface.

1. A method for collaborative matter management and analysis comprising: uploading a new document to a Master File in a computer system for collaborative matter management and analysis, wherein the Master File is a document repository for a matter; creating one or more metadata fields for said new document; extracting text from said document using text recognition; populating the one or more metadata fields with Players, document type and date associated with said new document; using said document type to determine if there are related documents and generating a structural hierarchy and placeholders for said related documents, wherein the structural hierarchy is based on timing; determining from said extracted text if said new document is an evidentiary document and adding a plurality of authentication metadata fields to said one or more metadata fields for authentication if said new document is evidentiary; determining from said extracted text if said new document is a version of an existing document in the system and associating said new document with said existing document upon positive determination; identifying all citations to evidentiary documents, Master File documents and legal authority documents in the new document; and converting said citations in said new document to hyperlinks to other documents in the system.

1. A method for collaborative matter management and analysis comprising: uploading a new document to a Master File in a computer system for collaborative matter management and analysis, wherein the Master File is a document repository for a matter; creating one or more metadata fields for said new document; extracting text from said document using text recognition; populating the one or more metadata fields with Players, document type and date associated with said new document; using said document type to determine if there are related documents and generating a structural hierarchy and placeholders for said related documents, wherein the structural hierarchy is based on timing; determining from said extracted text if said new document is an evidentiary document and adding a plurality of authentication metadata fields to said one or more metadata fields for authentication if said new document is evidentiary; determining from said extracted text if said new document is a version of an existing document in the system and associating said new document with said existing document upon positive determination; identifying all citations to evidentiary documents, Master File documents and legal authority documents in the new document; and converting said citations in said new document to hyperlinks to other documents in the system. 8. The method of claim 1 , wherein said one or more metadata fields comprises: an OCR field for storing said extracted text; an Evidence Tray for storing the citations to evidentiary documents; a Master File Tray for storing the citations to Master File documents; and a Legal Authority Tray for storing the citations to legal authority documents.

9. A method for focus navigation of a user interface in a computer system, comprising: receiving a single, discrete, directional input for changing the input focus from a current user interface object in the user interface, the single, discrete, directional input being received from an input device other than a mouse, wherein the single, discrete, directional input indicates a traversal direction selected by the user to indicate the direction of a user interface object desired by the user; selecting target candidates in the direction of travel indicated by the single discrete, directional input from among one or more user interface objects for receiving the input focus, and by: defining a selection region that includes at least an edge of the current user interface object in the direction of the single, discrete, directional input through a parallel edge of a display area; defining a baseline region within the selected region and which is a subset of the selection region; and selecting target candidates that overlap the selection region in the direction for the single, discrete, directional input and only when an edge opposite to the direction of the single, discrete, directional input overlaps the selection region; scoring the target candidates selected for receiving the input focus, wherein scoring the target candidates comprises: for all selected target candidates that at least partially overlap the baseline region, scoring them according to their perpendicular distance from an edge of the current user interface object, in a direction parallel to the direction of the single, discrete, directional input; and for all selected target candidates that do not overlap the baseline region, scoring them according to their radial distance from a point on a line partially defining one edge of the baseline region; and changing the input focus to a user interface object based upon the scoring.

9. A method for focus navigation of a user interface in a computer system, comprising: receiving a single, discrete, directional input for changing the input focus from a current user interface object in the user interface, the single, discrete, directional input being received from an input device other than a mouse, wherein the single, discrete, directional input indicates a traversal direction selected by the user to indicate the direction of a user interface object desired by the user; selecting target candidates in the direction of travel indicated by the single discrete, directional input from among one or more user interface objects for receiving the input focus, and by: defining a selection region that includes at least an edge of the current user interface object in the direction of the single, discrete, directional input through a parallel edge of a display area; defining a baseline region within the selected region and which is a subset of the selection region; and selecting target candidates that overlap the selection region in the direction for the single, discrete, directional input and only when an edge opposite to the direction of the single, discrete, directional input overlaps the selection region; scoring the target candidates selected for receiving the input focus, wherein scoring the target candidates comprises: for all selected target candidates that at least partially overlap the baseline region, scoring them according to their perpendicular distance from an edge of the current user interface object, in a direction parallel to the direction of the single, discrete, directional input; and for all selected target candidates that do not overlap the baseline region, scoring them according to their radial distance from a point on a line partially defining one edge of the baseline region; and changing the input focus to a user interface object based upon the scoring. 35. A computer-readable storage media storing computer-executable instructions that when executed perform the method of claim 9 .

17. The method of claim 16 , further comprising an act of iteratively repeating the search using the refined classifier and feature/attention model until the search goal is accomplished.

17. The method of claim 16 , further comprising an act of iteratively repeating the search using the refined classifier and feature/attention model until the search goal is accomplished. 18. The method of claim 17 , wherein in a case where the domain knowledge database contains no feature/attention models relating to the search goal, the act of searching is performed using unbiased, center-surround type saliency algorithms.

12. A computer-readable storage device instructions stored which, when executed by a server processor, cause the server processor to perform operations comprising: performing automatic speech recognition on an utterance received from a first party in a conversation, to yield recognized speech; determining a meaning of the utterance based, on the recognized speech; forming a query indicating the meaning of the utterance and based on a plurality of searching resources; sending the query based on the meaning of the query, to a plurality of relevant searching resources, in order to obtain first address links associated with search results of the plurality of relevant searching resources in response to the query, wherein the plurality of searching resources comprises a web-based search engine, local databases, and remote databases; sending the query to a device associated with a second party in the conversation for forwarding to at least one other relevant searching resource in order to second obtain address links; sending the first and second address links to the device; displaying the first and second address links on the device; selecting, by the second party, at least one address link from the first and second address links displayed relevant to the conversation and query; logging, the search results, a time and date of the query, the relevant searching resources searched during the conversation in response to the query, and the searching resources selected by the second party from the selected at least one address link to create a log; and presenting the log for analysis.

12. A computer-readable storage device instructions stored which, when executed by a server processor, cause the server processor to perform operations comprising: performing automatic speech recognition on an utterance received from a first party in a conversation, to yield recognized speech; determining a meaning of the utterance based, on the recognized speech; forming a query indicating the meaning of the utterance and based on a plurality of searching resources; sending the query based on the meaning of the query, to a plurality of relevant searching resources, in order to obtain first address links associated with search results of the plurality of relevant searching resources in response to the query, wherein the plurality of searching resources comprises a web-based search engine, local databases, and remote databases; sending the query to a device associated with a second party in the conversation for forwarding to at least one other relevant searching resource in order to second obtain address links; sending the first and second address links to the device; displaying the first and second address links on the device; selecting, by the second party, at least one address link from the first and second address links displayed relevant to the conversation and query; logging, the search results, a time and date of the query, the relevant searching resources searched during the conversation in response to the query, and the searching resources selected by the second party from the selected at least one address link to create a log; and presenting the log for analysis. 13. The computer-readable storage device of claim 12 , wherein the performing of automatic speech recognition further comprises creating text corresponding to the utterance.

16. A computer-implemented method for targeted sharing of information from an email message, comprising: identifying a personal email message selected by a user from an email message storage associated with an email client application; providing a recommendation of one or more shared wiki pages for the personal email message, comprising: comparing content of the personal email message with content of at least one shared wiki page; determining those shared wiki pages that are most similar to the personal email message; applying recommendation criteria to the most similar shared wiki pages and identifying the most similar shared wiki pages that satisfy the threshold as the recommended wiki pages; displaying the recommended wiki pages visually proximate to the personal email message in the email client application; receiving a selection of one of the recommended wiki pages from the user; and incorporating the personal email message into the selected recommended wiki page in the shared storage.

16. A computer-implemented method for targeted sharing of information from an email message, comprising: identifying a personal email message selected by a user from an email message storage associated with an email client application; providing a recommendation of one or more shared wiki pages for the personal email message, comprising: comparing content of the personal email message with content of at least one shared wiki page; determining those shared wiki pages that are most similar to the personal email message; applying recommendation criteria to the most similar shared wiki pages and identifying the most similar shared wiki pages that satisfy the threshold as the recommended wiki pages; displaying the recommended wiki pages visually proximate to the personal email message in the email client application; receiving a selection of one of the recommended wiki pages from the user; and incorporating the personal email message into the selected recommended wiki page in the shared storage. 20. A computer-implemented method according to claim 16 , wherein one of the recommended wiki pages is preselected by the user.

11. A machine-readable medium having stored thereon instructions which when executed by a processing device, cause the computing device to perform one or more operations comprising: receiving annotated data; parsing, at least partially, the annotated data, wherein parsing includes identifying syntactic structure of sentences within the annotated data; extracting training sets from the parsed annotated data, wherein the training sets are based on a plurality of features, wherein extracting comprises at least one of tagging the annotated data for marking words, and defining and segmenting words based on languages, wherein extracting further comprises extracting entity names and relations between entity names based on the information sets, and wherein extracting further comprises identifying information sets using memory-based Information Gain (IG)-Trees, wherein the IG-Trees are generated based on the plurality of features, wherein the plurality of features comprise one or more of words, phrases, sentences, and objects, and wherein each information set is identified based on a corresponding memory-based IG-Tree including one or more of a person-name IG-Tree, an entity-name IG-Tree, a noun phrase IG-Tree, and a relation IG-Tree.

11. A machine-readable medium having stored thereon instructions which when executed by a processing device, cause the computing device to perform one or more operations comprising: receiving annotated data; parsing, at least partially, the annotated data, wherein parsing includes identifying syntactic structure of sentences within the annotated data; extracting training sets from the parsed annotated data, wherein the training sets are based on a plurality of features, wherein extracting comprises at least one of tagging the annotated data for marking words, and defining and segmenting words based on languages, wherein extracting further comprises extracting entity names and relations between entity names based on the information sets, and wherein extracting further comprises identifying information sets using memory-based Information Gain (IG)-Trees, wherein the IG-Trees are generated based on the plurality of features, wherein the plurality of features comprise one or more of words, phrases, sentences, and objects, and wherein each information set is identified based on a corresponding memory-based IG-Tree including one or more of a person-name IG-Tree, an entity-name IG-Tree, a noun phrase IG-Tree, and a relation IG-Tree. 14. The machine-readable medium of claim 11 , wherein the training sets comprise one or more a first training set including words in names, a second training set including entity names, a third training set including phrases, and a fourth training set including relationships amongst the entities.

1. A computer implemented method of sharing information between a semantic network stored in a memory of a first computer system and a knowledge sharing repository, comprising: retrieving, from the semantic network, a set of data based on information included in the semantic network; accessing the knowledge sharing repository from the first computer system; and transferring, from the first computer system, the set of data to a computer system hosting the knowledge sharing repository for incorporation into the knowledge sharing repository.

1. A computer implemented method of sharing information between a semantic network stored in a memory of a first computer system and a knowledge sharing repository, comprising: retrieving, from the semantic network, a set of data based on information included in the semantic network; accessing the knowledge sharing repository from the first computer system; and transferring, from the first computer system, the set of data to a computer system hosting the knowledge sharing repository for incorporation into the knowledge sharing repository. 4. The method of claim 1 wherein said accessing the knowledge sharing repository comprises inserting a name of an entity into a URL or other access protocol for accessing an infobox for a desired page of the knowledge sharing repository.

14. The system of claim 10 , wherein the operations further include: searching, by the electronic device, for the search term within the plurality of documents, and displaying a plurality of pages, wherein the plurality of pages is selected so as to include pages from a plurality of different documents that include the search term.

14. The system of claim 10 , wherein the operations further include: searching, by the electronic device, for the search term within the plurality of documents, and displaying a plurality of pages, wherein the plurality of pages is selected so as to include pages from a plurality of different documents that include the search term. 15. The system of claim 14 , wherein the operations further include: receiving a selection of a displayed page of the plurality of pages, and, in response to receiving the selection of the displayed page, displaying a plurality of pages from a document associated with the selected displayed page.

1. A method, comprising: receiving, using a client device, a font subset comprising one or more glyphs of a master font having a master ordering that establishes an order of precedence on the glyphs of the master font; in response to said receiving, using the client device to reposition, in an extensible data structure, at least one glyph of one or more existing glyphs already in the extensible data structure, wherein prior to repositioning, the one or more existing glyphs are in a consecutive sequence in the extensible data structure to preserve the order of precedence established by the master ordering; and positioning, using the client device, each received glyph of the received font subset in the extensible data structure, wherein repositioning said at least one glyph and said positioning jointly establish a new consecutive sequential ordering on the glyphs of a combined font subset comprising the one or more existing glyphs and the one or more received glyphs of the received font subset, such that the new consecutive sequential ordering preserves, on the glyphs of the combined font subset, the order of precedence established by the master ordering.

1. A method, comprising: receiving, using a client device, a font subset comprising one or more glyphs of a master font having a master ordering that establishes an order of precedence on the glyphs of the master font; in response to said receiving, using the client device to reposition, in an extensible data structure, at least one glyph of one or more existing glyphs already in the extensible data structure, wherein prior to repositioning, the one or more existing glyphs are in a consecutive sequence in the extensible data structure to preserve the order of precedence established by the master ordering; and positioning, using the client device, each received glyph of the received font subset in the extensible data structure, wherein repositioning said at least one glyph and said positioning jointly establish a new consecutive sequential ordering on the glyphs of a combined font subset comprising the one or more existing glyphs and the one or more received glyphs of the received font subset, such that the new consecutive sequential ordering preserves, on the glyphs of the combined font subset, the order of precedence established by the master ordering. 5. The method of claim 1 , wherein the glyphs of the master font are partitioned into a plurality of master font ranges ranked in an order of precedence established by a master font range ordering, and wherein the one or more existing glyphs already in the extensible data structure are partitioned into one or more existing client font ranges consecutively enumerated to preserve the order of precedence established by the master font range ordering, wherein each of the one or more existing client font ranges corresponds to one of the plurality of master font ranges that contains each glyph in the existing client font range, the method further comprising: determining that at least one of the one or more existing client font ranges corresponds to a master font range which, in the master font range ordering, is preceded by another master font range containing a glyph of the requested font subset that is not contained in any of the one or more master font ranges corresponding to the one or more existing client font ranges, and in response to said determining: establishing one or more new client font ranges, wherein each of the one or more new client font ranges corresponds to one of the plurality of master font ranges containing a glyph of the requested font set that is not contained in any of the one or more master font ranges corresponding to the one or more existing client font ranges; consecutively enumerating a combined set of client font ranges comprising the one or more new client font ranges and the one or more existing client font ranges, wherein said consecutively enumerating the combined set shifts the at least one of the one or more existing client font ranges to a higher position while preserving the order of precedence established by the master font range ordering; and placing each of the glyphs of the combined font subset in the client font range whose corresponding master font range contains the glyph.

1. A speech recognition system, comprising: a distance calculation unit which generates a distance value between speech features, inputted sequentially, and each acoustic model; an acoustic lookahead unit which generates an acoustic lookahead value by using the distance value previously generated by the distance calculation unit, in parallel with generation of the distance value by the distance calculation unit; a word string matching unit which performs word matching by using the distance value previously generated by the distance calculation unit and the acoustic lookahead value previously generated by the acoustic lookahead unit to thereby generate a recognition result, in parallel with generation of the distance value by the distance calculation unit and generation of the acoustic lookahead value by the acoustic lookahead unit.

1. A speech recognition system, comprising: a distance calculation unit which generates a distance value between speech features, inputted sequentially, and each acoustic model; an acoustic lookahead unit which generates an acoustic lookahead value by using the distance value previously generated by the distance calculation unit, in parallel with generation of the distance value by the distance calculation unit; a word string matching unit which performs word matching by using the distance value previously generated by the distance calculation unit and the acoustic lookahead value previously generated by the acoustic lookahead unit to thereby generate a recognition result, in parallel with generation of the distance value by the distance calculation unit and generation of the acoustic lookahead value by the acoustic lookahead unit. 2. The speech recognition system, according to claim 1 , further comprising: distance value buffers which store distance values generated by the distance calculation unit; and acoustic lookahead value buffers which store acoustic lookahead values generated by the acoustic lookahead unit, wherein in each of the distance value buffers, operations of writing the distance value from the distance calculation unit, reading out the distance value to the acoustic lookahead unit, and reading out the distance value to the word string matching unit are performed, in each of the acoustic lookahead value buffers, operations of writing the acoustic lookahead value from the acoustic lookahead unit and reading out the acoustic lookahead value to the word string matching unit are performed, wherein, at any point in time, the distance value buffer in which the distance value from the distance calculation unit is written, the distance value buffer from which the distance value to the acoustic lookahead unit is read out, and the distance value buffer from which the distance value to the word string matching unit are read out, are different from one another, and the acoustic lookahead value buffer in which the acoustic lookahead value from the acoustic lookahead unit is written and the acoustic lookahead value buffer from which the acoustic lookahead value to the word string matching unit is read out are different from each other.

13. A non-transitory processor-readable memory having instructions stored thereon that, when executed, cause at least one processor to: extract an identified graphic from a document to provide an extracted graphic, wherein to extract the identified graphic from the document, the instructions are further to cause the at least one processor to: identify individual candidate reusable graphic components contained within the document; extract feature information and environmental information about each of the individual candidate reusable graphic components; evaluate the extracted information associated with each individual candidate reusable graphic component to determine whether the individual candidate reusable graphic components are to be consolidated into a single reusable graphic, wherein to evaluate the extracted feature information includes a plurality of: a first determining of whether a first of the individual candidate reusable graphic components is placed over a second of the individual candidate reusable graphic components in the document to determine whether the first and second individual candidate reusable graphic components are to be consolidated into a single reusable graphic; a second determining of whether the first individual candidate reusable graphic component is within a predetermined distance from the second individual candidate reusable graphic component in the document to determine whether the first and second individual candidate reusable graphic components are to be consolidated into a single reusable graphic; and a third determining of whether a third of the individual candidate reusable graphic components is between the first and the second individual candidate reusable graphic components to determine whether the first, second and third individual candidate reusable graphic components are to be consolidated into a single reusable graphic; and synthesize a single reusable graphic from the plurality of the first, second and third individual candidate reusable graphic components based on at least one of the first, second, and third determinations.

13. A non-transitory processor-readable memory having instructions stored thereon that, when executed, cause at least one processor to: extract an identified graphic from a document to provide an extracted graphic, wherein to extract the identified graphic from the document, the instructions are further to cause the at least one processor to: identify individual candidate reusable graphic components contained within the document; extract feature information and environmental information about each of the individual candidate reusable graphic components; evaluate the extracted information associated with each individual candidate reusable graphic component to determine whether the individual candidate reusable graphic components are to be consolidated into a single reusable graphic, wherein to evaluate the extracted feature information includes a plurality of: a first determining of whether a first of the individual candidate reusable graphic components is placed over a second of the individual candidate reusable graphic components in the document to determine whether the first and second individual candidate reusable graphic components are to be consolidated into a single reusable graphic; a second determining of whether the first individual candidate reusable graphic component is within a predetermined distance from the second individual candidate reusable graphic component in the document to determine whether the first and second individual candidate reusable graphic components are to be consolidated into a single reusable graphic; and a third determining of whether a third of the individual candidate reusable graphic components is between the first and the second individual candidate reusable graphic components to determine whether the first, second and third individual candidate reusable graphic components are to be consolidated into a single reusable graphic; and synthesize a single reusable graphic from the plurality of the first, second and third individual candidate reusable graphic components based on at least one of the first, second, and third determinations. 15. The non-transitory processor-readable memory of claim 13 , wherein the extracted information includes environment information about each identified individual candidate reusable graphic components.

4. A voice recognition apparatus according to claim 3, wherein said third means is a super net connected to said word net or said plurality of word nets for receiving all said values output from said word net or said plurality of word nets and for outputting said value corresponding to said classification of voice recognition in which said input utterance belongs.

4. A voice recognition apparatus according to claim 3, wherein said third means is a super net connected to said word net or said plurality of word nets for receiving all said values output from said word net or said plurality of word nets and for outputting said value corresponding to said classification of voice recognition in which said input utterance belongs. 5. A voice recognition apparatus according to claim 4, wherein each of said first, second and third means includes an input layer for receiving said values output from said plurality of event nets, a middle layer connected to each of said event nets respectively for receiving a first signal output from said input layer and for outputting a second signal produced by converting said first signal of said input layer using a sigmoid function, and an output layer for outputting said value corresponding to said similarity in said specific word with respect to said input utterance.

13. The system of claim 12 , further comprising: program code for converting said text to a code form that is readable by a clustering algorithm wherein the clustering algorithm groups into clusters examples of events that are similar to each other; and program code for passing said code form to said clustering algorithm.

13. The system of claim 12 , further comprising: program code for converting said text to a code form that is readable by a clustering algorithm wherein the clustering algorithm groups into clusters examples of events that are similar to each other; and program code for passing said code form to said clustering algorithm. 15. The system of claim 13 , wherein said program code for converting converts events in the database into examples for said clustering algorithm.

1. A method for static detection and categorization of information-flow downgraders, comprising: transforming a program stored in a memory device by statically analyzing program variables to yield a single assignment for each variable in an instruction set; translating the instruction set to production rules with string operations to identify a finite set of strings; generating a context-free grammar from the production rules; and identifying an information-flow downgrader function by checking the finite set of strings against one or more function specifications, wherein the information-flow downgrader function downgrades input information by endorsing integrity and declassifying confidentiality of the information to enable high input information to flow to low program points.

1. A method for static detection and categorization of information-flow downgraders, comprising: transforming a program stored in a memory device by statically analyzing program variables to yield a single assignment for each variable in an instruction set; translating the instruction set to production rules with string operations to identify a finite set of strings; generating a context-free grammar from the production rules; and identifying an information-flow downgrader function by checking the finite set of strings against one or more function specifications, wherein the information-flow downgrader function downgrades input information by endorsing integrity and declassifying confidentiality of the information to enable high input information to flow to low program points. 6. The method as recited in claim 1 , wherein the one or more function specifications are employed to categorize the downgrader function.

1. A method comprising: receiving a user-submitted query originating from a user; and in response to receiving the user-submitted query, and prior to returning search results associated with the user-submitted query: identifying a plurality of candidate queries, without further input from the user; for each candidate query, without further input from the user: extracting three or more features, each feature reflecting a measurement of effectiveness of the candidate query with respect to the user-submitted query, wherein the three or more features including an estimated normalized discounted cumulative gain, wherein the measurement of effectiveness of the candidate query based, at least in part, on a match feature that reflects how well the candidate query matches search results of the candidate query, a cross match feature that reflects how well the user-submitted query matches search results of the candidate query, and a similarity feature that reflects similarities between search results of the user-submitted query and search results of the candidate query; and generating a feature vector that includes each of the three or more features as individual components of the feature vector; rank ordering the candidate queries based at least in part on the feature vectors of the candidate queries; and suggesting one or more of the top-ranked candidate queries as alternate queries for the user-submitted query.

1. A method comprising: receiving a user-submitted query originating from a user; and in response to receiving the user-submitted query, and prior to returning search results associated with the user-submitted query: identifying a plurality of candidate queries, without further input from the user; for each candidate query, without further input from the user: extracting three or more features, each feature reflecting a measurement of effectiveness of the candidate query with respect to the user-submitted query, wherein the three or more features including an estimated normalized discounted cumulative gain, wherein the measurement of effectiveness of the candidate query based, at least in part, on a match feature that reflects how well the candidate query matches search results of the candidate query, a cross match feature that reflects how well the user-submitted query matches search results of the candidate query, and a similarity feature that reflects similarities between search results of the user-submitted query and search results of the candidate query; and generating a feature vector that includes each of the three or more features as individual components of the feature vector; rank ordering the candidate queries based at least in part on the feature vectors of the candidate queries; and suggesting one or more of the top-ranked candidate queries as alternate queries for the user-submitted query. 8. A method as recited in claim 1 , wherein rank ordering the candidate queries based at least in part on the feature vectors comprises: learning a ranking model based on training data; and applying the ranking model to the feature vectors for each of the candidate queries.

1. A computer-implemented method comprising: maintaining a user profile for each of a plurality of users of a social networking system, each user profile comprising a set of attributes; selecting a user from the plurality of users; receiving user profile information for at least one user of a set of users in the social networking system who are connected to the selected user in the social networking system; inferring a value of one or more attributes of the user profile for the selected user based on information describing the set of users who are connected to the selected user in the social networking system; comparing a confidence score value for an inferred user profile attribute to a threshold value; storing, responsive to the confidence score being above the threshold value, the inferred value of the user profile attribute with the user profile for the selected user; determining relevant information for the selected user based on the inferred user profile attribute; and sending the relevant information to the selected user.

1. A computer-implemented method comprising: maintaining a user profile for each of a plurality of users of a social networking system, each user profile comprising a set of attributes; selecting a user from the plurality of users; receiving user profile information for at least one user of a set of users in the social networking system who are connected to the selected user in the social networking system; inferring a value of one or more attributes of the user profile for the selected user based on information describing the set of users who are connected to the selected user in the social networking system; comparing a confidence score value for an inferred user profile attribute to a threshold value; storing, responsive to the confidence score being above the threshold value, the inferred value of the user profile attribute with the user profile for the selected user; determining relevant information for the selected user based on the inferred user profile attribute; and sending the relevant information to the selected user. 12. The computer-implemented method of claim 1 , wherein the set of users is determined based on the attribute being inferred for the selected user.

1. A system comprising: one or more processors; memory; and one or more computer-executable instructions that are stored in the memory and that are executable by the one or more processors to: access audio signals of a conversation between a customer and a customer service (CS) agent; track attributes of the audio signals, one or more attributes of the attributes quantifying aspects of the conversation based at least in part on words spoken by the customer and the CS agent; determine that the one or more attributes include one or more pauses greater than a threshold amount of time; determine mood imagery based at least in part on the one or more attributes, the mood imagery indicating a first estimation of a state of mind of the customer during a first time period of the conversation; determine that the mood imagery includes a first facial expression, the first facial expression being selected from a plurality of facial expressions based at least in part on analyzing the one or more attributes and being associated with the first estimation of the state of mind of the customer; generate a first communication suggestion for the CS agent based at least in part on analyzing the conversation and the first estimation of the state of mind of the customer, the first communication suggestion including a first suggestion to at least one of decrease a rate of speech, or use a word or utterance less frequently; generate a first time series graph indicating a measured element associated with the one or more attributes, the one or more attributes including at least one of a volume, a pitch, or a speed of spoken words of at least the CS agent; generate a second time series graph indicating a score for the CS agent, the score based at least in part on aggregating the attributes, the attributes including the volume, the pitch, and the speed of the spoken words; and cause first visual output of the mood imagery, the first time series graph, the second time series graph, and the first communication suggestion for view by the CS agent, wherein the mood imagery includes the first facial expression being updated in real-time or near real-time based at least in part on a change of the first estimation of the state of mind of the customer.

1. A system comprising: one or more processors; memory; and one or more computer-executable instructions that are stored in the memory and that are executable by the one or more processors to: access audio signals of a conversation between a customer and a customer service (CS) agent; track attributes of the audio signals, one or more attributes of the attributes quantifying aspects of the conversation based at least in part on words spoken by the customer and the CS agent; determine that the one or more attributes include one or more pauses greater than a threshold amount of time; determine mood imagery based at least in part on the one or more attributes, the mood imagery indicating a first estimation of a state of mind of the customer during a first time period of the conversation; determine that the mood imagery includes a first facial expression, the first facial expression being selected from a plurality of facial expressions based at least in part on analyzing the one or more attributes and being associated with the first estimation of the state of mind of the customer; generate a first communication suggestion for the CS agent based at least in part on analyzing the conversation and the first estimation of the state of mind of the customer, the first communication suggestion including a first suggestion to at least one of decrease a rate of speech, or use a word or utterance less frequently; generate a first time series graph indicating a measured element associated with the one or more attributes, the one or more attributes including at least one of a volume, a pitch, or a speed of spoken words of at least the CS agent; generate a second time series graph indicating a score for the CS agent, the score based at least in part on aggregating the attributes, the attributes including the volume, the pitch, and the speed of the spoken words; and cause first visual output of the mood imagery, the first time series graph, the second time series graph, and the first communication suggestion for view by the CS agent, wherein the mood imagery includes the first facial expression being updated in real-time or near real-time based at least in part on a change of the first estimation of the state of mind of the customer. 5. The system as recited in claim 1 , wherein the computer-executable instructions are further executable by the one or more processors to output a visual post-communication summary that is based at least in part on statistics generated from at least the one or more attributes of the conversation.

1. A method for navigating through selection modes for a displayed representation of computational construct that represents a terminal operand, the selection modes including a left selection mode, a tree selection mode, and a right selection mode, the method comprising: setting a current selection to a selection of the computational construct representing the terminal operand in the left selection mode so that, when a further computational construct representing a binary operator is specified, the terminal operand will be a right operand of the binary operator; when the current selection is the selection of the computational construct representing the terminal operand in the left selection mode and a user inputs a first indicator, setting the current selection to a selection of the computational construct representing the terminal operand in the tree selection mode so that, when a further computational construct is specified, the computational construct representing the terminal operand is replaced by the specified computational construct; and when the current selection is the selection of the computational construct representing the terminal operand in the tree selection mode and the user inputs the first indicator, setting the current selection to a selection of the computational construct representing the terminal operand in the right selection mode so that, when a further computational construct representing a binary operator is specified, the terminal operand will be a left operand of the binary operator.

1. A method for navigating through selection modes for a displayed representation of computational construct that represents a terminal operand, the selection modes including a left selection mode, a tree selection mode, and a right selection mode, the method comprising: setting a current selection to a selection of the computational construct representing the terminal operand in the left selection mode so that, when a further computational construct representing a binary operator is specified, the terminal operand will be a right operand of the binary operator; when the current selection is the selection of the computational construct representing the terminal operand in the left selection mode and a user inputs a first indicator, setting the current selection to a selection of the computational construct representing the terminal operand in the tree selection mode so that, when a further computational construct is specified, the computational construct representing the terminal operand is replaced by the specified computational construct; and when the current selection is the selection of the computational construct representing the terminal operand in the tree selection mode and the user inputs the first indicator, setting the current selection to a selection of the computational construct representing the terminal operand in the right selection mode so that, when a further computational construct representing a binary operator is specified, the terminal operand will be a left operand of the binary operator. 5. The method of claim 1, further comprising: when the current selection is the selection of the computational construct representing the terminal operand in the left selection mode and the user inputs a second indicator, setting the current selection to a selection of a parent computational construct of the computational construct representing the terminal operand in the tree selection mode.

1. A computer-implemented method comprising: receiving a path expression to be evaluated on an encoded XML data source, wherein the encoded XML data source is defined by an XML schema, wherein the path expression comprises path expression steps, each path expression step of said path expression steps specifying at least a characteristic of an element or an element attribute, wherein the encoded XML data source comprises an encoded representation of a particular element encoded within said encoded XML data source; prior to evaluating the encoded XML data source, compiling the path expression, thereby forming a compiled path expression, wherein the compiled path expression comprises a representation of a path expression step of the path expression, said representation of a path expression step of the path expression including said encoded representation of a particular element; wherein the compiled path expression also comprises a parsing instruction associated with the representation of the path expression step of the path expression; wherein compiling the path expression comprises: based on analyzing the XML schema, determining a portion of the encoded XML data source that cannot match the path expression step, and generating the parsing instruction to skip said portion of the encoded XML data source; evaluating the compiled path expression on the encoded XML data source, wherein evaluating the compiled path expression includes skipping a portion of the encoded XML data source, based on the parsing instruction, without evaluating whether said portion of the encoded XML data source matches against the path expression step; and generating a result based on the evaluation of the path expression.

1. A computer-implemented method comprising: receiving a path expression to be evaluated on an encoded XML data source, wherein the encoded XML data source is defined by an XML schema, wherein the path expression comprises path expression steps, each path expression step of said path expression steps specifying at least a characteristic of an element or an element attribute, wherein the encoded XML data source comprises an encoded representation of a particular element encoded within said encoded XML data source; prior to evaluating the encoded XML data source, compiling the path expression, thereby forming a compiled path expression, wherein the compiled path expression comprises a representation of a path expression step of the path expression, said representation of a path expression step of the path expression including said encoded representation of a particular element; wherein the compiled path expression also comprises a parsing instruction associated with the representation of the path expression step of the path expression; wherein compiling the path expression comprises: based on analyzing the XML schema, determining a portion of the encoded XML data source that cannot match the path expression step, and generating the parsing instruction to skip said portion of the encoded XML data source; evaluating the compiled path expression on the encoded XML data source, wherein evaluating the compiled path expression includes skipping a portion of the encoded XML data source, based on the parsing instruction, without evaluating whether said portion of the encoded XML data source matches against the path expression step; and generating a result based on the evaluation of the path expression. 10. The method of claim 1 , wherein the path expression step indicates that it is to be matched to an element of a particular name, and wherein the compiled representation of the path expression step does not include information indicating any name.

1. A method to identify an emotion evoked by media, the method comprising: accessing a pre-verbal utterance known to evoke a first emotion; creating, using a musical instrument digital interface notator, a musical instrument digital interface representation of the pre-verbal utterance; synthesizing, using a digital musical instrument, a first synthesized sample based on the musical instrument digital interface representation of the pre-verbal utterance; calculating, with a processor, a first value of a first feature of the first synthesized sample; creating, with the processor, a mood model based on the first feature, the mood model to establish a relationship between the first value of the first feature and the first emotion; identifying a second value of the first feature of first media evoking an unknown emotion; and identifying the unknown emotion as the first emotion when the mood model indicates that the second value corresponds to the first value.

1. A method to identify an emotion evoked by media, the method comprising: accessing a pre-verbal utterance known to evoke a first emotion; creating, using a musical instrument digital interface notator, a musical instrument digital interface representation of the pre-verbal utterance; synthesizing, using a digital musical instrument, a first synthesized sample based on the musical instrument digital interface representation of the pre-verbal utterance; calculating, with a processor, a first value of a first feature of the first synthesized sample; creating, with the processor, a mood model based on the first feature, the mood model to establish a relationship between the first value of the first feature and the first emotion; identifying a second value of the first feature of first media evoking an unknown emotion; and identifying the unknown emotion as the first emotion when the mood model indicates that the second value corresponds to the first value. 10. The method as described in claim 1 , further including: identifying a brand associated with the first emotion; and generating an integrated advertisement identifying the brand; and presenting the integrated advertisement at a same time as the first media.

1. A network node comprising: a network interface configured for transferring an identified flow of data packets, associated with an application service and having been output by an application server, toward a destination device according to an open network protocol and based on selected network parameters, the network interface further configured for transferring between the application server and the destination device at least one message having XML tags specifying prescribed user-selected quality of service attributes for the application service, the network node distinct from the destination device and the application server; an extensible markup language (XML) parser configured for parsing the XML tags for the prescribed user-selected quality of service attributes; and an application resource configured for interpreting the XML tags and the prescribed user-selected quality of service attributes and selecting the selected network parameters based on the interpreting of the prescribed user-selected quality of service attributes, causing the network interface to transfer the identified flow of data packets for the application service between the application server and the destination device according to the user-selected quality of service attributes based on the selected network parameters.

1. A network node comprising: a network interface configured for transferring an identified flow of data packets, associated with an application service and having been output by an application server, toward a destination device according to an open network protocol and based on selected network parameters, the network interface further configured for transferring between the application server and the destination device at least one message having XML tags specifying prescribed user-selected quality of service attributes for the application service, the network node distinct from the destination device and the application server; an extensible markup language (XML) parser configured for parsing the XML tags for the prescribed user-selected quality of service attributes; and an application resource configured for interpreting the XML tags and the prescribed user-selected quality of service attributes and selecting the selected network parameters based on the interpreting of the prescribed user-selected quality of service attributes, causing the network interface to transfer the identified flow of data packets for the application service between the application server and the destination device according to the user-selected quality of service attributes based on the selected network parameters. 11. The network node of claim 1 , wherein the message further includes second XML tags specifying prescribed application server-selected service attributes for the corresponding application service, based on a group of predetermined server-selected XML tags specifying respective service attributes identifiable by the application resource, the application resource configured for selecting, for each corresponding predetermined server-selected XML tag, a corresponding prescribed network parameter for implementation of the corresponding service attribute.

21. The apparatus of claim 20 , wherein the action header field indicates an action, the prerequisite field specifies any prerequisites needed to perform the action, the sub-action field specifies any sub-actions which are needed to complete execution of the action, and the action effect field specifies a result of execution of the action.

21. The apparatus of claim 20 , wherein the action header field indicates an action, the prerequisite field specifies any prerequisites needed to perform the action, the sub-action field specifies any sub-actions which are needed to complete execution of the action, and the action effect field specifies a result of execution of the action. 22. The apparatus of claim 21 , wherein the action planning unit determines whether or not a prerequisite included in the action data corresponding to the logical command is satisfied, and wherein if the result of determining whether or not a prerequisite included in the action data corresponding to the logical command is satisfied indicates that the prerequisite is not satisfied and an action capable of satisfying the prerequisite is not in the action library, the action planning unit outputs an error message.

9. A computer-implemented method for providing an information navigation system for searching a set of materials having navigation states, the method comprising: providing information including: the set of materials, a plurality of attributes characterizing the materials, a plurality of values describing the materials, each value of the values having an association with at least one attribute of the attributes, each association defining an attribute-value pair, and a plurality of navigation states, each navigation state corresponding to a particular set of attribute-value pairs and to a particular subset of materials, wherein the particular subset of materials consists of materials in the information navigation system that are described by every attribute-value pair in the particular set of attribute-value pairs corresponding to said each navigation state, such that each material of materials in the particular subset of materials is described by every attribute-value pair in the particular set of attribute-value pairs corresponding to said each navigation state; using a data structure in a memory to permit at least some navigation states of the plurality of navigation states to be computed dynamically, wherein a first navigation state of the computed navigation states includes a first attribute-value pair having a first attribute, in which the first attribute-value pair does not describe all the materials in the navigation system that the first attribute characterizes, wherein a second navigation state of the computed navigation states includes a second attribute-value pair having the first attribute, in which the second attribute-value pair refines the first attribute-value pair, and wherein at least one of the first navigation state and the second navigation state includes a third attribute-value pair having a third attribute, which is not the same as the first attribute, wherein the third attribute-value pair is mutually incomparable with the first attribute-value pair and is mutually incomparable with the second attribute-value pair, and the third attribute-value pair does not describe all the materials in the navigation system that the third attribute characterizes; providing an interface to the navigation system, the interface including a free-text search tool, and the interface providing a plurality of transitions, each transition providing a direct path, with no intervening navigation states, between two of the navigation states, wherein said each transition represents a change from a set of attribute-value pairs corresponding to an originating navigation state to the set of attribute-value pairs corresponding to a destination navigation state, wherein series of one or more transitions provides a path between any two navigation states, there being more than one path between at least a third navigation state and a fourth navigation state, wherein the interface includes a guided search tool for enabling navigation from a current navigation state based on the plurality of transitions among the plurality of navigation states, and wherein the interface operates in an XML-based environment; searching, by using a computer, descriptive information associated with the set of materials, based at least in part on a free-text query accepted from the free-text search tool of the provided interface, to produce a set of free-text query interpretations; accepting a query to the information navigation system based at least in part on the free-text query interpretations; generating a responsive navigation state using the data structure based on the query; and presenting the responsive navigation state to a user.

9. A computer-implemented method for providing an information navigation system for searching a set of materials having navigation states, the method comprising: providing information including: the set of materials, a plurality of attributes characterizing the materials, a plurality of values describing the materials, each value of the values having an association with at least one attribute of the attributes, each association defining an attribute-value pair, and a plurality of navigation states, each navigation state corresponding to a particular set of attribute-value pairs and to a particular subset of materials, wherein the particular subset of materials consists of materials in the information navigation system that are described by every attribute-value pair in the particular set of attribute-value pairs corresponding to said each navigation state, such that each material of materials in the particular subset of materials is described by every attribute-value pair in the particular set of attribute-value pairs corresponding to said each navigation state; using a data structure in a memory to permit at least some navigation states of the plurality of navigation states to be computed dynamically, wherein a first navigation state of the computed navigation states includes a first attribute-value pair having a first attribute, in which the first attribute-value pair does not describe all the materials in the navigation system that the first attribute characterizes, wherein a second navigation state of the computed navigation states includes a second attribute-value pair having the first attribute, in which the second attribute-value pair refines the first attribute-value pair, and wherein at least one of the first navigation state and the second navigation state includes a third attribute-value pair having a third attribute, which is not the same as the first attribute, wherein the third attribute-value pair is mutually incomparable with the first attribute-value pair and is mutually incomparable with the second attribute-value pair, and the third attribute-value pair does not describe all the materials in the navigation system that the third attribute characterizes; providing an interface to the navigation system, the interface including a free-text search tool, and the interface providing a plurality of transitions, each transition providing a direct path, with no intervening navigation states, between two of the navigation states, wherein said each transition represents a change from a set of attribute-value pairs corresponding to an originating navigation state to the set of attribute-value pairs corresponding to a destination navigation state, wherein series of one or more transitions provides a path between any two navigation states, there being more than one path between at least a third navigation state and a fourth navigation state, wherein the interface includes a guided search tool for enabling navigation from a current navigation state based on the plurality of transitions among the plurality of navigation states, and wherein the interface operates in an XML-based environment; searching, by using a computer, descriptive information associated with the set of materials, based at least in part on a free-text query accepted from the free-text search tool of the provided interface, to produce a set of free-text query interpretations; accepting a query to the information navigation system based at least in part on the free-text query interpretations; generating a responsive navigation state using the data structure based on the query; and presenting the responsive navigation state to a user. 36. The method of claim 9 , wherein the interface operates in a World Wide Web-based environment.

11. A computerized process comprising: receiving at a computer processor data relating to a composition of a target group; receiving at the computer processor logged communications of the target group; extracting with the computer processor textual information from the logged communications; analyzing with the computer processor the textual information using statistical and linguistic sentiment analysis techniques; generating one or more vectors from the analysis of the textual information; combining one or more assessments from multiple vectors; identifying with the computer processor an individual or sub-group from the target group as a function of the analysis of the textual information; and causing to be displayed on a user interface or transmitting to another processor the identified individual or sub-group of the target group and causing to be displayed on the user interface or transmitting to another processor a sentiment assessment of the identified individual or sub-group as a function of the statistical and linguistic sentiment analysis; wherein the logged communications are a database of recorded audio voices; and wherein the system comprises a processor configured to analyze the one or more recorded audio voices for audio voice characteristics; and wherein the one or more processors are further configured to analyze the sentiment of the individual or sub-group over a period of time.

11. A computerized process comprising: receiving at a computer processor data relating to a composition of a target group; receiving at the computer processor logged communications of the target group; extracting with the computer processor textual information from the logged communications; analyzing with the computer processor the textual information using statistical and linguistic sentiment analysis techniques; generating one or more vectors from the analysis of the textual information; combining one or more assessments from multiple vectors; identifying with the computer processor an individual or sub-group from the target group as a function of the analysis of the textual information; and causing to be displayed on a user interface or transmitting to another processor the identified individual or sub-group of the target group and causing to be displayed on the user interface or transmitting to another processor a sentiment assessment of the identified individual or sub-group as a function of the statistical and linguistic sentiment analysis; wherein the logged communications are a database of recorded audio voices; and wherein the system comprises a processor configured to analyze the one or more recorded audio voices for audio voice characteristics; and wherein the one or more processors are further configured to analyze the sentiment of the individual or sub-group over a period of time. 12. The computerized process of claim 11 , wherein the data relating to a composition of a target group comprises one or more of a one to many relationship or a many to many relationship.

27. A method for generating a first package such that an application may be automatically executed by a browser on a client computer, the method comprising: generating a first archive of files that include instructions and content needed to execute the application, the first archive including: an initial file that includes instructions for initiating execution of the application, the initial file being a markup language file, other files needed to execute the application, and a second package that includes a second manifest and a second archive of files, the second package being of the same type as the first package, and the second archive of files being of the same type of file structure as the first archive of files; generating a first manifest file that is associated with the first archive, the first manifest file including an initial file identifier that instructs the browser to process the initial file before processing other files in the first archive in order to initiate execution of the application; and encapsulating the first archive of files and the first manifest file within the first package.

27. A method for generating a first package such that an application may be automatically executed by a browser on a client computer, the method comprising: generating a first archive of files that include instructions and content needed to execute the application, the first archive including: an initial file that includes instructions for initiating execution of the application, the initial file being a markup language file, other files needed to execute the application, and a second package that includes a second manifest and a second archive of files, the second package being of the same type as the first package, and the second archive of files being of the same type of file structure as the first archive of files; generating a first manifest file that is associated with the first archive, the first manifest file including an initial file identifier that instructs the browser to process the initial file before processing other files in the first archive in order to initiate execution of the application; and encapsulating the first archive of files and the first manifest file within the first package. 32. The method of claim 27 , wherein: the first manifest file further comprises an archive type identifier that instructs the browser to process the instructions for initiating execution of the application from the initial file in accordance with the application type of the application.

1. A method implemented in a programmable system for reasonable functional verification of a design of an integrated circuit (IC), the method comprising: retrieving from storage by the programmable system a description of the design of at least a portion of the IC; causing the programmable system to bring at least a portion of the IC in the received description to a state close to a suspected point of failure through analysis of a setup for failure (SFF) property; executing by the programmable system functional verification of at least a portion of the design of the IC from the suspected point of failure through analysis of a trigger for failure (TFF) property; and providing by the programmable system a report respective of a result of the executing of the set of instructions.

1. A method implemented in a programmable system for reasonable functional verification of a design of an integrated circuit (IC), the method comprising: retrieving from storage by the programmable system a description of the design of at least a portion of the IC; causing the programmable system to bring at least a portion of the IC in the received description to a state close to a suspected point of failure through analysis of a setup for failure (SFF) property; executing by the programmable system functional verification of at least a portion of the design of the IC from the suspected point of failure through analysis of a trigger for failure (TFF) property; and providing by the programmable system a report respective of a result of the executing of the set of instructions. 12. The method of claim 1 , further comprising reporting by the programmable system failure to reach a desired SFF property.

2. The method according to claim 1 , comprising displaying the captured image, and f) digital image filtering of the captured image including contrast enhancement, shadow compensation, unwarping and rotation of the captured image in order to obtain an artifact reduced image with a substantially horizontal text alignment, wherein the detection of the plurality of word blocks is based on the artifact reduced image; g) performing OCR within each word block to get its text content; h) assigning to each A-block an attribute; i) indicating the A-blocks in the display by a frame or a background color and displaying their attributes as overlays within the artifact reduced and displayed image for the selection of the keyword; j) the selection of the A-block containing the keyword being based on the displayed attribute of the keyword; and k) upon the selection of the A-block, displaying the text content of the selected A-block.

2. The method according to claim 1 , comprising displaying the captured image, and f) digital image filtering of the captured image including contrast enhancement, shadow compensation, unwarping and rotation of the captured image in order to obtain an artifact reduced image with a substantially horizontal text alignment, wherein the detection of the plurality of word blocks is based on the artifact reduced image; g) performing OCR within each word block to get its text content; h) assigning to each A-block an attribute; i) indicating the A-blocks in the display by a frame or a background color and displaying their attributes as overlays within the artifact reduced and displayed image for the selection of the keyword; j) the selection of the A-block containing the keyword being based on the displayed attribute of the keyword; and k) upon the selection of the A-block, displaying the text content of the selected A-block. 15. The method according to claim 2 , wherein (c) comprises the detection of text-parts within the captured and artifact reduced image which get designated by attributes within step (h), whereupon within (j) one of the text-parts is selectable whereupon the text-part gets OCR converted and used as text input.

8. A method of choosing a language to be used by a text disambiguation function executed by an electronic device, the electronic device being operable to send messages to and receive messages from at least two recipients, the method comprising: determining that a message being drafted is an original message; examining language tags associated with each of at least two of the recipients; and automatically selecting a language for the original message based on the examined language tags, regardless of the number of languages represented by the examined language tags.

8. A method of choosing a language to be used by a text disambiguation function executed by an electronic device, the electronic device being operable to send messages to and receive messages from at least two recipients, the method comprising: determining that a message being drafted is an original message; examining language tags associated with each of at least two of the recipients; and automatically selecting a language for the original message based on the examined language tags, regardless of the number of languages represented by the examined language tags. 11. The method of claim 8 , wherein when a predetermined percentage of the at least two recipients of the message do not share a common preferred language tag or a common secondary language tag, the selected language is a default language.

1. A computer-implemented method for providing on a display a rich media themed search results webpage, the method comprising the steps of: receiving a search query at a search engine; obtaining one or more search results from the search engine based on the search query; analyzing the search query received at the search engine; accessing one or more rich-media-theme databases storing rich-media themes that are interactive, visual backgrounds useable to enhance a display of the one or more search results; comparing the search query and the rich media themes stored in the one or more rich-media-theme databases; selecting a rich-media theme that correlates to the search query, wherein the selection of a rich-media theme is based on one or more user's device characteristics; providing a plurality of layers in which one or more components of the search results display are displayed in a top layer, and one or more components of the rich media theme are displayed in one or more background layers; and composing a search results webpage by stacking the layers to create a unified display in which at least a portion of each layer is visible through an overlying layer, the rich media theme being displayed in an ambient manner that does not obstruct a user's view of the search results display, and the rich media theme being representative of the subject matter of the search query and user's device characteristics.

1. A computer-implemented method for providing on a display a rich media themed search results webpage, the method comprising the steps of: receiving a search query at a search engine; obtaining one or more search results from the search engine based on the search query; analyzing the search query received at the search engine; accessing one or more rich-media-theme databases storing rich-media themes that are interactive, visual backgrounds useable to enhance a display of the one or more search results; comparing the search query and the rich media themes stored in the one or more rich-media-theme databases; selecting a rich-media theme that correlates to the search query, wherein the selection of a rich-media theme is based on one or more user's device characteristics; providing a plurality of layers in which one or more components of the search results display are displayed in a top layer, and one or more components of the rich media theme are displayed in one or more background layers; and composing a search results webpage by stacking the layers to create a unified display in which at least a portion of each layer is visible through an overlying layer, the rich media theme being displayed in an ambient manner that does not obstruct a user's view of the search results display, and the rich media theme being representative of the subject matter of the search query and user's device characteristics. 5. The computer implemented method of claim 1 , wherein the rich media theme is selected based a direct correlation to at least one search term.

1. A computerized medical self-diagnostic system comprising: a memory in a computing device configured to store a data structure, wherein data in the data structure is referenced by specification of a plurality of attributes representative of a medical condition of a patient; an interface configured to receive at least one attribute via a direct interactive dialogue between a patient and the computing device, wherein the data structure remains unchanged by the receiving at least one attribute via direct interactive dialogue, wherein a first stored attribute corresponds to a cause of disease and a second stored attribute corresponds to an anatomic system stored in said data structure; and a processor in a computing device, in data communication with the memory, configured to make a self-diagnosis of a new and changing health condition of and to the patient without input from a health care provider based on the data in the data structure and the specification of at least one attribute determined via said direct interactive dialogue.

1. A computerized medical self-diagnostic system comprising: a memory in a computing device configured to store a data structure, wherein data in the data structure is referenced by specification of a plurality of attributes representative of a medical condition of a patient; an interface configured to receive at least one attribute via a direct interactive dialogue between a patient and the computing device, wherein the data structure remains unchanged by the receiving at least one attribute via direct interactive dialogue, wherein a first stored attribute corresponds to a cause of disease and a second stored attribute corresponds to an anatomic system stored in said data structure; and a processor in a computing device, in data communication with the memory, configured to make a self-diagnosis of a new and changing health condition of and to the patient without input from a health care provider based on the data in the data structure and the specification of at least one attribute determined via said direct interactive dialogue. 7. The system of claim 1 , wherein the data structure is a two-dimensional array.

1. A method comprising: generating a new message in response to a command, wherein the new message relates to a message thread; storing words found in messages associated with the message thread as language objects in a dictionary of language objects associated with the message thread; and associating frequency values with the language objects in the dictionary to prioritize the language objects in the dictionary over words not contained in the dictionary.

1. A method comprising: generating a new message in response to a command, wherein the new message relates to a message thread; storing words found in messages associated with the message thread as language objects in a dictionary of language objects associated with the message thread; and associating frequency values with the language objects in the dictionary to prioritize the language objects in the dictionary over words not contained in the dictionary. 5. The method of claim 1 , wherein the dictionary of language objects is located in a first portion of a memory separate from a generic word list located in a second portion of the memory.

24. An article comprising a machine readable storage device that stores executable instructions for determining an appropriate response to an input, the instructions causing a processor to: link a plurality of attributes to a plurality of response templates using a plurality of Boolean expressions, each attribute associated with a set of patterns, each pattern within the set of patterns being equivalent; receive the input; and determine an appropriate response template for the received input, the appropriate response template selected from the plurality of response templates based on the input, by instructions to: determine matches of the input to patterns; rank the patterns; and select the corresponding response template based on the ranked patterns .

24. An article comprising a machine readable storage device that stores executable instructions for determining an appropriate response to an input, the instructions causing a processor to: link a plurality of attributes to a plurality of response templates using a plurality of Boolean expressions, each attribute associated with a set of patterns, each pattern within the set of patterns being equivalent; receive the input; and determine an appropriate response template for the received input, the appropriate response template selected from the plurality of response templates based on the input, by instructions to: determine matches of the input to patterns; rank the patterns; and select the corresponding response template based on the ranked patterns . 25. The article of claim 24 , wherein instructions causing a machine to determine comprises: performing an initialization.

1. An energy harvesting communication device configured with on chip signal booster apparatus; comprising: at least a communication apparatus; at least an antenna apparatus in association with an input and/or output device; at least a processor in communication with at least one of: said at least a communication apparatus; said at least an antenna apparatus; a charge platform in association with at least charging circuit; at least an interactive media in association with at least an interactive interface; an output device; and at least a sensor apparatus embedded in silicon substrate and etched and/or fused in nano-fiber and/or microfiber material, said at least a sensor apparatus in association with said at least a communication apparatus to provide at least one of an effective energy harvesting medium, communication clarity, communication medium, detection selectivity medium, and detection platform.

1. An energy harvesting communication device configured with on chip signal booster apparatus; comprising: at least a communication apparatus; at least an antenna apparatus in association with an input and/or output device; at least a processor in communication with at least one of: said at least a communication apparatus; said at least an antenna apparatus; a charge platform in association with at least charging circuit; at least an interactive media in association with at least an interactive interface; an output device; and at least a sensor apparatus embedded in silicon substrate and etched and/or fused in nano-fiber and/or microfiber material, said at least a sensor apparatus in association with said at least a communication apparatus to provide at least one of an effective energy harvesting medium, communication clarity, communication medium, detection selectivity medium, and detection platform. 36. The energy harvesting communication device of claim 1 , wherein said sensor apparatus further comprises at least one of: an accelerometer; a proximity sensor; a detection apparatus; a sensor network; a media detection network; video management network; image management network.

25. A software shell as claimed in claim 24 wherein the at least one knowledge source module includes: a rule-based knowledge source module having a forward-chaining belief propagation scheme including rules in if-then-else form with associated levels of belief; and a case-based knowledge source module having a data comparison scheme including predefined patterns and conditions, whereupon execution of the case-based knowledge source, the conditions are inferred to be true if a certain level of closeness is found between received data and the patterns.

25. A software shell as claimed in claim 24 wherein the at least one knowledge source module includes: a rule-based knowledge source module having a forward-chaining belief propagation scheme including rules in if-then-else form with associated levels of belief; and a case-based knowledge source module having a data comparison scheme including predefined patterns and conditions, whereupon execution of the case-based knowledge source, the conditions are inferred to be true if a certain level of closeness is found between received data and the patterns. 32. A software shell as claimed in claim 25 further including: a blackboard structure description file including object names and attribute/value pairs for each object; a rule-based description file including rules forming the rule-based knowledge source and a description of execution preconditions for the rule-based knowledge source; a case-based description file including cases forming the case-based knowledge source and a description of execution preconditions for the case-based knowledge source; wherein the blackboard structure description file, rule-based description file, case-based description file, and input data file are user created.

41. The method of claim 40 , wherein ranking the graph nodes comprises sorting the sentences in reverse order based upon the second plurality of scores.

41. The method of claim 40 , wherein ranking the graph nodes comprises sorting the sentences in reverse order based upon the second plurality of scores. 42. The method of claim 41 , wherein selecting at least one of the plurality of sentences comprises selecting a selected number of sentences having the highest rankings.

15. The method of claim 8 , further comprising: providing a means by which a user can customize content and/or a format of the template.

15. The method of claim 8 , further comprising: providing a means by which a user can customize content and/or a format of the template. 16. The method of claim 15 , wherein providing a means by which a user can customize content of the template comprises: providing a means by which a user can add or remove one or more of the fields to be populated within the template.

6. A method comprising: under control of one or more processors configured with executable instructions, receiving a content item comprising a first body of text, the first body of text comprising at least a first text portion and a second text portion; training a classifier based at least in part on an annotated text portion of a second body of text, the annotated text portion having been associated with a first reason through a user interaction received by a computing device associated with a first user, wherein the first body of text is different from the second body of text, and wherein, once trained, the classifier is configured to assign scores indicating a probability that a corresponding portion of the first text portion will be annotated by a second user based on the annotated text portion of the second body of text; assigning, using the trained classifier, and to the first text portion, a first score that indicates the probability that the first text portion will be annotated by the second user; assigning, using the trained classifier, and to the second text portion, a second score that indicates the probability that the second text portion will be annotated by the second user, wherein the first score and the second score are assigned based at least in part on the annotated text portion; ranking, based at least in part on the first score and the second score, the at least the first text portion and the second text portion of the first body of text; And selecting at least one of the first text portion or the second text portion based at least in part on the raking.

6. A method comprising: under control of one or more processors configured with executable instructions, receiving a content item comprising a first body of text, the first body of text comprising at least a first text portion and a second text portion; training a classifier based at least in part on an annotated text portion of a second body of text, the annotated text portion having been associated with a first reason through a user interaction received by a computing device associated with a first user, wherein the first body of text is different from the second body of text, and wherein, once trained, the classifier is configured to assign scores indicating a probability that a corresponding portion of the first text portion will be annotated by a second user based on the annotated text portion of the second body of text; assigning, using the trained classifier, and to the first text portion, a first score that indicates the probability that the first text portion will be annotated by the second user; assigning, using the trained classifier, and to the second text portion, a second score that indicates the probability that the second text portion will be annotated by the second user, wherein the first score and the second score are assigned based at least in part on the annotated text portion; ranking, based at least in part on the first score and the second score, the at least the first text portion and the second text portion of the first body of text; And selecting at least one of the first text portion or the second text portion based at least in part on the raking. 16. The method as recited in claim 6 , wherein the body of text is from a content item, the method further comprising sending information related to the ranking to an author of the content item.

14. The method of claim 1 , further comprising: searching contextual identifiers in the at least one data structure, wherein the searching comprises: receiving the search query; comparing contextual identifiers in the at least one data structure with the search query; identifying, responsive to the search query, the one or more contextual identifiers associated with the indication of the call; and returning at least one of the one or more contextual identifiers and an indication of the call, for display, at the graphical user interface associated with the communication device.

14. The method of claim 1 , further comprising: searching contextual identifiers in the at least one data structure, wherein the searching comprises: receiving the search query; comparing contextual identifiers in the at least one data structure with the search query; identifying, responsive to the search query, the one or more contextual identifiers associated with the indication of the call; and returning at least one of the one or more contextual identifiers and an indication of the call, for display, at the graphical user interface associated with the communication device. 16. The method of claim 14 , wherein searching the contextual identifiers in the at least one data structure comprises: determining, by the communication device, a confidence value that indicates a likelihood that search query matches at least one of the one or more contextual identifiers; and when the confidence value is greater than a predetermined value, selecting, by the communication device, the at least one of the one or more contextual identifiers.

1. A method of developing one or more application programs that cooperate to manage a distributed system comprising one or more servers, wherein at least one application program is associated with each server, the method including the steps: a) defining one or more managed objects associated with the distributed system in an object-oriented resource definition language and storing the definition of the one or more managed objects in one or more resource definition language files, wherein the definition of the one or more managed objects is based on an existing design and hierarchical structure of the distributed system, wherein parent-child relationships between the one or more managed objects are identified in the one or more resource definition language files using the object-oriented resource definition language to define the one or more managed objects in relation to the hierarchical structure of the distributed system; b) parsing the one or more resource definition language files to ensure conformity with the object-oriented resource definition language and creating an intermediate representation of the distributed system from the one or more conforming resource definition language files; c) processing the intermediate representation of the distributed system to form one or more programming language classes, one or more database definition files, and one or more script files; d) providing a reusable asset center framework to facilitate development of the one or more application programs, the reusable asset center including an SNMP agent framework that provides SNMP interface functionality to at least one of the one or more application programs, wherein the SNMP agent framework includes an SNMP table management object framework class that converts SNMP requests to managed object framework commands and an SNMP table class that includes procedures for accessing and chancing data in tables; and e) building the one or more application programs from at least the one or more programming language classes, one or more database definition files, one or more script files, and the reusable asset framework.

1. A method of developing one or more application programs that cooperate to manage a distributed system comprising one or more servers, wherein at least one application program is associated with each server, the method including the steps: a) defining one or more managed objects associated with the distributed system in an object-oriented resource definition language and storing the definition of the one or more managed objects in one or more resource definition language files, wherein the definition of the one or more managed objects is based on an existing design and hierarchical structure of the distributed system, wherein parent-child relationships between the one or more managed objects are identified in the one or more resource definition language files using the object-oriented resource definition language to define the one or more managed objects in relation to the hierarchical structure of the distributed system; b) parsing the one or more resource definition language files to ensure conformity with the object-oriented resource definition language and creating an intermediate representation of the distributed system from the one or more conforming resource definition language files; c) processing the intermediate representation of the distributed system to form one or more programming language classes, one or more database definition files, and one or more script files; d) providing a reusable asset center framework to facilitate development of the one or more application programs, the reusable asset center including an SNMP agent framework that provides SNMP interface functionality to at least one of the one or more application programs, wherein the SNMP agent framework includes an SNMP table management object framework class that converts SNMP requests to managed object framework commands and an SNMP table class that includes procedures for accessing and chancing data in tables; and e) building the one or more application programs from at least the one or more programming language classes, one or more database definition files, one or more script files, and the reusable asset framework. 6. The method as set forth in claim 1 wherein the SNMP agent framework includes an SNMP table management object framework class, an object identifier converter class, an SNMP object stream class, an SNMP object stream finder class, an SNMP toolkit class, an SNMP table class, a managed object framework agent class, an SNMP table MAS class, and an object stream class.

1. A computer implemented method for creating visual content originating from a document comprising a plurality of pages to be output in a layered manner, the method comprising: a) receiving a document that comprises at least one image content item and at least one textual content item; b) categorizing the at least one image content item into at least one first category, and the at least one textual content item into a second category representing textual content in the plurality of pages in the received document; c) manipulating image content data of the at least one image content item of the at least one first category with at least one operation applicable for image content, and creating at least one image data file comprising manipulated image data based on said manipulated image content data for at least one image layer for display on a client device; d) re-constructing the textual content items in the second category representing textual content in the plurality of pages in the received document into a single logical entity, e) manipulating re-constructed textual content data of the at least one textual content item of the second category representing textual content in the plurality of pages in the received document, comprising the sub-steps of: analyzing the re-constructed textual content data representing textual content in the plurality of pages in the received document re-constructed in the single logical entity, and creating web font variants for the textual content in the plurality of pages in the document for different software applications based on an output of said analyzing, and creating a text data file comprising manipulated textual content data for a text layer to be prepared for display on the client device; and f) storing the at least one image data file comprising the manipulated image data and the text data file comprising the manipulated textual content data.

1. A computer implemented method for creating visual content originating from a document comprising a plurality of pages to be output in a layered manner, the method comprising: a) receiving a document that comprises at least one image content item and at least one textual content item; b) categorizing the at least one image content item into at least one first category, and the at least one textual content item into a second category representing textual content in the plurality of pages in the received document; c) manipulating image content data of the at least one image content item of the at least one first category with at least one operation applicable for image content, and creating at least one image data file comprising manipulated image data based on said manipulated image content data for at least one image layer for display on a client device; d) re-constructing the textual content items in the second category representing textual content in the plurality of pages in the received document into a single logical entity, e) manipulating re-constructed textual content data of the at least one textual content item of the second category representing textual content in the plurality of pages in the received document, comprising the sub-steps of: analyzing the re-constructed textual content data representing textual content in the plurality of pages in the received document re-constructed in the single logical entity, and creating web font variants for the textual content in the plurality of pages in the document for different software applications based on an output of said analyzing, and creating a text data file comprising manipulated textual content data for a text layer to be prepared for display on the client device; and f) storing the at least one image data file comprising the manipulated image data and the text data file comprising the manipulated textual content data. 4. The computer implemented method as claimed in claim 1 , wherein the manipulation of the textual content data comprises a step of selecting a font to be used in the text layer.

19. The non-transitory machine-readable storage medium of claim 18 , wherein the operations further comprise buffering a portion of the audio component to generate a buffered portion, and wherein the converting the audio component comprises converting the buffered portion.

19. The non-transitory machine-readable storage medium of claim 18 , wherein the operations further comprise buffering a portion of the audio component to generate a buffered portion, and wherein the converting the audio component comprises converting the buffered portion. 20. The non-transitory machine-readable storage medium of claim 19 , wherein the buffered portion is converted using the speech recognition.

1. A system for managing the separate control of resource usage and resource access for interoperability between and within open, distributed computing environments, comprising: a client computer comprising a processor including both a usage management mechanism and an enforcement mechanism, the usage management mechanism for managing resource usage according to a context, an event, and a license, the license including a set of actions and a policy specifying the conditions for whether or not the event may occur, and the enforcement mechanism for enforcing the license within the system according to how the license may be used; a server computer comprising a processor including a license generator managing resource access according to the policy using a license object and a context object, the license object identifying content usage policies and the context object identifying a structure and state of the computing environment, a model deployed within each of the open, distributed computing environments, the model using generic rights expression language lic, C, umm, iav, EM, for interoperability of the license within the computing environment, the license object represented by lic= Racv, ε, I with Racv representing restricted actions in the computing environment according to the license, ε representing the license that is subject to the restricted actions, and I representing a set of functions supported by the license capturing the dynamic usage history in the computing environment associated with the policy, the context object represented by C= E, S, R , with E representing a set of system environment properties, S representing a set of subject properties, and R representing a set of resource properties capturing the dynamic state of the computing environment through attributes of each entity within the computing environment; the usage management mechanism represented by umm= UI, Act, iC with UI representing functions used by the usage management mechanism to interact with the license, Act representing all actions enabled in the computing environments, and iC representing an instance of the context, wherein the usage management mechanism of the client computer queries the license object and the context object of the server computer for compatibility of the event with the policy and the client computer accepts the event and accesses content when the policy is compatible, wherein an activity by the client computer on the content generates an activity instance iav= acv, iC with acv representing the activity and iC representing the instance of the context; the enforcement mechanism represented by EM= A, iC, U with A representing the set of actions performed under the license, iC representing the instance of the context, and U representing functions of the license that are used by the enforcement mechanism to interact with the license, wherein the enforcement mechanism of the client computer prevents the activity on the content when the activity is not compatible with the set of actions of the license.

1. A system for managing the separate control of resource usage and resource access for interoperability between and within open, distributed computing environments, comprising: a client computer comprising a processor including both a usage management mechanism and an enforcement mechanism, the usage management mechanism for managing resource usage according to a context, an event, and a license, the license including a set of actions and a policy specifying the conditions for whether or not the event may occur, and the enforcement mechanism for enforcing the license within the system according to how the license may be used; a server computer comprising a processor including a license generator managing resource access according to the policy using a license object and a context object, the license object identifying content usage policies and the context object identifying a structure and state of the computing environment, a model deployed within each of the open, distributed computing environments, the model using generic rights expression language lic, C, umm, iav, EM, for interoperability of the license within the computing environment, the license object represented by lic= Racv, ε, I with Racv representing restricted actions in the computing environment according to the license, ε representing the license that is subject to the restricted actions, and I representing a set of functions supported by the license capturing the dynamic usage history in the computing environment associated with the policy, the context object represented by C= E, S, R , with E representing a set of system environment properties, S representing a set of subject properties, and R representing a set of resource properties capturing the dynamic state of the computing environment through attributes of each entity within the computing environment; the usage management mechanism represented by umm= UI, Act, iC with UI representing functions used by the usage management mechanism to interact with the license, Act representing all actions enabled in the computing environments, and iC representing an instance of the context, wherein the usage management mechanism of the client computer queries the license object and the context object of the server computer for compatibility of the event with the policy and the client computer accepts the event and accesses content when the policy is compatible, wherein an activity by the client computer on the content generates an activity instance iav= acv, iC with acv representing the activity and iC representing the instance of the context; the enforcement mechanism represented by EM= A, iC, U with A representing the set of actions performed under the license, iC representing the instance of the context, and U representing functions of the license that are used by the enforcement mechanism to interact with the license, wherein the enforcement mechanism of the client computer prevents the activity on the content when the activity is not compatible with the set of actions of the license. 2. The system according to claim 1 , wherein the context further comprises a constraint, wherein the constraint is a set of restrictions over the context.

2. The method of claim 1 wherein using superoptimization to automatically generate the set of peephole translation rules comprises: i) extracting objective instruction sequences from a set of training programs executable on the source ISA; ii) matching the objective instructions sequences with equivalent candidate instruction sequences executable on the target ISA using superoptimization techniques; and iii) generating peephole translation rules from the matches.

2. The method of claim 1 wherein using superoptimization to automatically generate the set of peephole translation rules comprises: i) extracting objective instruction sequences from a set of training programs executable on the source ISA; ii) matching the objective instructions sequences with equivalent candidate instruction sequences executable on the target ISA using superoptimization techniques; and iii) generating peephole translation rules from the matches. 3. The method of claim 2 wherein the equivalent candidate instruction sequences are determined with consideration to a register map from the source ISA state to the target ISA state.

21. A prosody structure generation apparatus comprising: a dialog information database which manages an entire dialog between a user and a system, and stores information and a dialog history required for the dialog to proceed based on a speech acts and intention; a system speaking style determination unit which determines a speech act and intention by analyzing a user utterance obtained through a speech recognition process with reference to the dialog information database, and determines the system speaking style as either read speech or dialog speech according to the determined speech act and intention associated with the user utterance; and a dialog prosody generation unit including a discourse information generation unit, a prosody information generation unit, and an intonation pattern generation unit, wherein the discourse information generation unit receives a user utterance from the system speaking style determination unit and generates a discourse information structure in which a different emphasis part is set according to whether the speech act and included semantic unit of a system utterance corresponding to whether the user utterance is new information or old information, wherein the prosody information generation unit receives discourse information structure from the discourse information generation unit, and a semantic structure, a sentence structure, and a morpheme structure of a system utterance, and generates prosody information in which an emphasis tag including an utterance boundary level, accent, and utterance duration is set on the basis of the types of semantic words, a closeness between polymorphemes, and a number of syllables that can be spoken at a time, wherein the utterance boundary level is adjusted based on closeness between semantic units, which is determined by syntax and case, and wherein the intonation pattern generation unit receives inputs of the semantic structure of a system utterance including prosody information, extracts a plurality of characteristics in each semantic unit and compares the plurality of characteristics with the characteristics of each semantic unit of an intonation pattern database with contents of characteristics of each semantic unit and their index, searches for a semantic unit having closest characteristics, and generates an intonation pattern according to a result of the search using by at least one computer system, wherein the speech act provides a speech act classification of the user utterance, so that even when speech acts are identical, the generated intonation pattern varies according to the speech act classification of the user utterance.

21. A prosody structure generation apparatus comprising: a dialog information database which manages an entire dialog between a user and a system, and stores information and a dialog history required for the dialog to proceed based on a speech acts and intention; a system speaking style determination unit which determines a speech act and intention by analyzing a user utterance obtained through a speech recognition process with reference to the dialog information database, and determines the system speaking style as either read speech or dialog speech according to the determined speech act and intention associated with the user utterance; and a dialog prosody generation unit including a discourse information generation unit, a prosody information generation unit, and an intonation pattern generation unit, wherein the discourse information generation unit receives a user utterance from the system speaking style determination unit and generates a discourse information structure in which a different emphasis part is set according to whether the speech act and included semantic unit of a system utterance corresponding to whether the user utterance is new information or old information, wherein the prosody information generation unit receives discourse information structure from the discourse information generation unit, and a semantic structure, a sentence structure, and a morpheme structure of a system utterance, and generates prosody information in which an emphasis tag including an utterance boundary level, accent, and utterance duration is set on the basis of the types of semantic words, a closeness between polymorphemes, and a number of syllables that can be spoken at a time, wherein the utterance boundary level is adjusted based on closeness between semantic units, which is determined by syntax and case, and wherein the intonation pattern generation unit receives inputs of the semantic structure of a system utterance including prosody information, extracts a plurality of characteristics in each semantic unit and compares the plurality of characteristics with the characteristics of each semantic unit of an intonation pattern database with contents of characteristics of each semantic unit and their index, searches for a semantic unit having closest characteristics, and generates an intonation pattern according to a result of the search using by at least one computer system, wherein the speech act provides a speech act classification of the user utterance, so that even when speech acts are identical, the generated intonation pattern varies according to the speech act classification of the user utterance. 22. The apparatus of claim 21 , wherein the dialog information database expresses system utterances corresponding to user utterances that are input, according to the speech act and intention, and stores the system utterances as elements of a database.

21. A software application development tool for assembling applications in which a check-in terminal communicates with two or more airline systems and services, the software application development tool stored on non-transitory computer readable media and comprising computer readable program code comprising: a common code base, wherein the common code base is incompatible with the two or more airline systems and services; data and messages used by the application described using a declarative data description language; a library of system components including: a) a terminal abstraction layer that allows interactions between the check-in terminal and the application to control the check-in terminal; and b) an airline systems and services abstraction layer that allows interactions between the two or more airline systems and services and the application, wherein the two or more airline systems and services comprise check-in systems; a graphical (GUI) tool to model the workflow of the application, the workflow including screens and services described declaratively by a declarative data description language; and an assembler for assembling the application using the graphical tool, declarative rules, and customizations of the system components selected from the library.

21. A software application development tool for assembling applications in which a check-in terminal communicates with two or more airline systems and services, the software application development tool stored on non-transitory computer readable media and comprising computer readable program code comprising: a common code base, wherein the common code base is incompatible with the two or more airline systems and services; data and messages used by the application described using a declarative data description language; a library of system components including: a) a terminal abstraction layer that allows interactions between the check-in terminal and the application to control the check-in terminal; and b) an airline systems and services abstraction layer that allows interactions between the two or more airline systems and services and the application, wherein the two or more airline systems and services comprise check-in systems; a graphical (GUI) tool to model the workflow of the application, the workflow including screens and services described declaratively by a declarative data description language; and an assembler for assembling the application using the graphical tool, declarative rules, and customizations of the system components selected from the library. 39. A software application development tool according to claim 21 , wherein the check-in terminal comprises an agent device.

2. The method of claim 1 , wherein creating the index further comprises: adding a set of token data values to a token list, each token data value in the set representing an individual attribute in the structured data; and passing each token data value in the token list to a first Bloom filter in the set.

2. The method of claim 1 , wherein creating the index further comprises: adding a set of token data values to a token list, each token data value in the set representing an individual attribute in the structured data; and passing each token data value in the token list to a first Bloom filter in the set. 3. The method of claim 2 , further comprising: sorting the token data values in the token list using one or more specified sorting rules; appending a plurality of the token data values in the token list to form a concatenated token; and passing the concatenated token to a second Bloom filter in the set.

1. A method for determining a language spoken in an audio segment, from a multiplicity of languages, the method comprising the steps of: a. receiving the audio segment; b. performing acoustical language identification to yield an at least one estimated languages spoken in the audio segment; c. performing speech to text on the audio segment to yield estimated text, using a speech to text engine of a selected language of the at least one estimated languages; d. extracting a linguistic feature or statistical data from the estimated text; e. verifying whether the estimated text is in the selected language according to the linguistic feature or statistical data; f. if the estimated text is in the selected language, outputting the selected language as the language spoken in the audio segment; g. if the estimated text is not in the selected language, selecting another language from the at least one estimated languages and repeating steps c, d, e, f and g; and h. if there are no more estimated languages, outputting that the language of the audio segment is not one of the multiplicity of languages.

1. A method for determining a language spoken in an audio segment, from a multiplicity of languages, the method comprising the steps of: a. receiving the audio segment; b. performing acoustical language identification to yield an at least one estimated languages spoken in the audio segment; c. performing speech to text on the audio segment to yield estimated text, using a speech to text engine of a selected language of the at least one estimated languages; d. extracting a linguistic feature or statistical data from the estimated text; e. verifying whether the estimated text is in the selected language according to the linguistic feature or statistical data; f. if the estimated text is in the selected language, outputting the selected language as the language spoken in the audio segment; g. if the estimated text is not in the selected language, selecting another language from the at least one estimated languages and repeating steps c, d, e, f and g; and h. if there are no more estimated languages, outputting that the language of the audio segment is not one of the multiplicity of languages. 2. The method of claim 1 further comprising an acoustic model generation or enhancement step for generating or enhancing an at least one acoustic model associated with each of the multiplicity of languages, for performing the acoustical language identification.

11. A computer-implemented system, comprising: one or more processors; and one or more non-transitory computer-readable storage mediums containing instructions configured to cause the one or more processors to perform operations including: receiving a structured query in a structured query language; determining a schema that defines a structure for unstructured data, wherein the schema identifies a plurality of fields in the unstructured data; conducting a pilot query on the unstructured data, wherein the pilot query is conducted using the schema, and wherein conducting the pilot query identifies one or more fields in the unstructured data; converting the structured query in the structured query language into an unstructured query in an unstructured query language, wherein the conversion is done using the one or more fields identified by conducting the pilot query, and wherein the unstructured query is used to access the unstructured data; conducting a search on the unstructured data using the unstructured query; caching the one or more fields identified by conducting the pilot query; conducting a new pilot query on the unstructured data, wherein conducting the new pilot query identifies one or more new fields in the unstructured data; and merging the one or more cached fields with the one or more new fields.

11. A computer-implemented system, comprising: one or more processors; and one or more non-transitory computer-readable storage mediums containing instructions configured to cause the one or more processors to perform operations including: receiving a structured query in a structured query language; determining a schema that defines a structure for unstructured data, wherein the schema identifies a plurality of fields in the unstructured data; conducting a pilot query on the unstructured data, wherein the pilot query is conducted using the schema, and wherein conducting the pilot query identifies one or more fields in the unstructured data; converting the structured query in the structured query language into an unstructured query in an unstructured query language, wherein the conversion is done using the one or more fields identified by conducting the pilot query, and wherein the unstructured query is used to access the unstructured data; conducting a search on the unstructured data using the unstructured query; caching the one or more fields identified by conducting the pilot query; conducting a new pilot query on the unstructured data, wherein conducting the new pilot query identifies one or more new fields in the unstructured data; and merging the one or more cached fields with the one or more new fields. 18. The system of claim 11 , further comprising instructions configured to cause the one or more processors to perform operations including: presenting results of the search.

1. A computer-implemented method comprising: receiving, at a computing device having one or more processors, a collection of documents; clustering, at the computing device, the documents into one or more clusters; generating, at the computing device, a cluster vector for each cluster of the one or more clusters; generating, at the computing device, a target vector associated with a target profile, the target profile being associated with an identified user; storing, at the computing device, the target profile; comparing, at the computing device, the target vector with each of the cluster vectors; selecting, at the computing device, one or more of the one or more clusters based on the comparison of the target vector with each of the cluster vectors; and generating, at the computing device, a custom language model for the identified user using documents from the one or more selected clusters.

1. A computer-implemented method comprising: receiving, at a computing device having one or more processors, a collection of documents; clustering, at the computing device, the documents into one or more clusters; generating, at the computing device, a cluster vector for each cluster of the one or more clusters; generating, at the computing device, a target vector associated with a target profile, the target profile being associated with an identified user; storing, at the computing device, the target profile; comparing, at the computing device, the target vector with each of the cluster vectors; selecting, at the computing device, one or more of the one or more clusters based on the comparison of the target vector with each of the cluster vectors; and generating, at the computing device, a custom language model for the identified user using documents from the one or more selected clusters. 3. The method of claim 1 , where each cluster is associated with a topic or domain.

205. A method comprising: receiving first activity information for a sender of a first link to at least one recipient collected by a collection resource at a Web site, wherein no personally identifiable information of the sender is collected in the first activity information; storing the first activity information at a storage server; receiving second activity information when a recipient accesses the first link sent by the sender corresponding to the first activity information stored at the storage server, wherein no personally identifiable information of the recipient is collected in the second activity information; using at least one processor, using the first activity information to identify a first node in a social graph as being representative of the sender further comprising: extracting a user identifier from the first activity data; and if a match for the user identifier is not found in the social graph, attempting to match a plurality of mobile device identifiers in a selected geo-vicinity and selected time interval; using the second activity information to identify a second node in the social graph as being representative of the recipient; determining a category for the first link as a first category type; in the social graph, identifying a first edge between the first and second nodes as being representative of the first category type; and updating a first value associated with the first edge to a second value based on a time elapsed from at least one of the first activity information or second activity information.

205. A method comprising: receiving first activity information for a sender of a first link to at least one recipient collected by a collection resource at a Web site, wherein no personally identifiable information of the sender is collected in the first activity information; storing the first activity information at a storage server; receiving second activity information when a recipient accesses the first link sent by the sender corresponding to the first activity information stored at the storage server, wherein no personally identifiable information of the recipient is collected in the second activity information; using at least one processor, using the first activity information to identify a first node in a social graph as being representative of the sender further comprising: extracting a user identifier from the first activity data; and if a match for the user identifier is not found in the social graph, attempting to match a plurality of mobile device identifiers in a selected geo-vicinity and selected time interval; using the second activity information to identify a second node in the social graph as being representative of the recipient; determining a category for the first link as a first category type; in the social graph, identifying a first edge between the first and second nodes as being representative of the first category type; and updating a first value associated with the first edge to a second value based on a time elapsed from at least one of the first activity information or second activity information. 212. The method of claim 205 wherein the collection resource at a Web site used to collect first activity information comprises a URL shortening.

8. A computer storage device having computer-executable instructions for blending recorded speech with text-to-speech (TTS) for specific domains, comprising: receiving input text; identifying a domain from the input text that identifies a type of speech application; determining a static part from the input text that has previously been recorded and stored within a data store, wherein determining the static part comprises detecting the static part based on recorded units for the identified domain; determining a dynamic part from the input text; and blending the static part with the dynamic part within a TTS engine.

8. A computer storage device having computer-executable instructions for blending recorded speech with text-to-speech (TTS) for specific domains, comprising: receiving input text; identifying a domain from the input text that identifies a type of speech application; determining a static part from the input text that has previously been recorded and stored within a data store, wherein determining the static part comprises detecting the static part based on recorded units for the identified domain; determining a dynamic part from the input text; and blending the static part with the dynamic part within a TTS engine. 12. The computer storage device of claim 8 , further comprising splitting a portion of identified non-uniform units from the input text into a transition part and a central part and adjusting the transition part to smooth a transition between uniform units.

1. A method for providing to a user a context menu with entries representing relationships, wherein the entries are selectable by the user to relate a plurality of objects selected from a set of objects, the method comprising: receiving a first identification of a first selected object from the set of objects; receiving a second identification of a second selected object from the set of objects; identifying object types of the selected objects in a plurality of object types; determining one or more relationship types requiring at least one object of the object type of the first selected object and at least one object of the object type of the second selected object as input in order to be created as a relationship between objects; and generating for the context menu an entry for creating a relationship of the one or more relationship types, wherein the entry is selectable by the user to create the relationship between the selected objects, and wherein the relationship changes an attribute of each object.

1. A method for providing to a user a context menu with entries representing relationships, wherein the entries are selectable by the user to relate a plurality of objects selected from a set of objects, the method comprising: receiving a first identification of a first selected object from the set of objects; receiving a second identification of a second selected object from the set of objects; identifying object types of the selected objects in a plurality of object types; determining one or more relationship types requiring at least one object of the object type of the first selected object and at least one object of the object type of the second selected object as input in order to be created as a relationship between objects; and generating for the context menu an entry for creating a relationship of the one or more relationship types, wherein the entry is selectable by the user to create the relationship between the selected objects, and wherein the relationship changes an attribute of each object. 5. The method of claim 1 further comprising: upon having received the second identification of the second object, receiving one or more further identifications of selected objects from the set of objects.

1. A method of searching for a query object within an object class, said method comprising: (a) accessing a collection of unique training samples of multiple training objects within said object class; (b) defining a separate training set of training item descriptors from each of said training samples; (c) extracting the training item descriptors from the separate training sets into a single composite collection of individual training item descriptors; (d) creating a hierarchical tree from said composite collection of individual training item descriptors according to relations in the individual training item descriptors, said hierarchical tree having a plurality of leaf nodes; (e) accessing registration sets of registration item descriptors, each registration set being defined from a respective registration sample obtained from a registration objects to be registered, said registration object being of said object class, individually distributing each registration item descriptor from each registration set into said hierarchical tree according to said relations defined in the creation of said hierarchical tree, indexing the registration item descriptors clustered within each leaf node to their corresponding registration samples; (f) defining a separate registration model for each registration sample based on the clustering of its corresponding registration item descriptors in each leaf node; (g) accessing a query sample from said query object, defining a query set of query item descriptors from said query sample, individually distributing each query item descriptor into said hierarchical tree according to said relations defined in the creation of said hierarchical tree; (h) defining a query model for said query sample based on the clustering of said query item descriptors in each leaf node; and (i) using the query model, x, and the registration models to identify as a potential candidate match the registration object, i, that renders the highest confidence i* of matching the query object, defined as i*=arg max i P(x|i)P(i).

1. A method of searching for a query object within an object class, said method comprising: (a) accessing a collection of unique training samples of multiple training objects within said object class; (b) defining a separate training set of training item descriptors from each of said training samples; (c) extracting the training item descriptors from the separate training sets into a single composite collection of individual training item descriptors; (d) creating a hierarchical tree from said composite collection of individual training item descriptors according to relations in the individual training item descriptors, said hierarchical tree having a plurality of leaf nodes; (e) accessing registration sets of registration item descriptors, each registration set being defined from a respective registration sample obtained from a registration objects to be registered, said registration object being of said object class, individually distributing each registration item descriptor from each registration set into said hierarchical tree according to said relations defined in the creation of said hierarchical tree, indexing the registration item descriptors clustered within each leaf node to their corresponding registration samples; (f) defining a separate registration model for each registration sample based on the clustering of its corresponding registration item descriptors in each leaf node; (g) accessing a query sample from said query object, defining a query set of query item descriptors from said query sample, individually distributing each query item descriptor into said hierarchical tree according to said relations defined in the creation of said hierarchical tree; (h) defining a query model for said query sample based on the clustering of said query item descriptors in each leaf node; and (i) using the query model, x, and the registration models to identify as a potential candidate match the registration object, i, that renders the highest confidence i* of matching the query object, defined as i*=arg max i P(x|i)P(i). 9. The method of claim 1 , wherein in step (f), each registration model is a histogram the numbers of its corresponding registration item descriptors in each leaf node.

15. A computer readable storage medium comprising computer executable instructions that when executed via a processor perform a method, the method comprising: obtaining a set of phrases for presentation as a function of one or more characters entered into a character entry field, at least one phrase within the set of phrases comprising more than one term; pinning one or more terms, but fewer than all terms, of a presented phrase, from the set of phrases, the pinned terms inserted into the character entry field; and temporarily replacing one or more pinned terms in the character entry field, but fewer than all pinned terms, with a placeholder when a second set of phrases, obtained based at least in part upon the pinned terms, comprises fewer than a desired number of phrases.

15. A computer readable storage medium comprising computer executable instructions that when executed via a processor perform a method, the method comprising: obtaining a set of phrases for presentation as a function of one or more characters entered into a character entry field, at least one phrase within the set of phrases comprising more than one term; pinning one or more terms, but fewer than all terms, of a presented phrase, from the set of phrases, the pinned terms inserted into the character entry field; and temporarily replacing one or more pinned terms in the character entry field, but fewer than all pinned terms, with a placeholder when a second set of phrases, obtained based at least in part upon the pinned terms, comprises fewer than a desired number of phrases. 20. The computer readable storage medium of claim 15 , comprising distinguishing one or more terms of a phrase presented in the set of phrases differently than other terms in the phrase, the distinguished one or more terms indicative of terms that may be pinned.

17. The system of claim 11 , wherein the first utterance is received through a first device and the second utterance is received through a second device, wherein the first device and the second device are connected to the user equipment via a network.

17. The system of claim 11 , wherein the first utterance is received through a first device and the second utterance is received through a second device, wherein the first device and the second device are connected to the user equipment via a network. 18. The system of claim 17 , wherein the control circuitry configured to determine the first context and second context of at least one of the first media asset and the second media asset is further configured to: identify a first user profile associated with the first user on the first device and a second profile associated with a second user on the second device; retrieve, from the first user profile, a first plurality of media assets previously viewed by the first user; retrieve, from the second user profile, a second plurality of media assets previously viewed by the second user; determine the first context and the second context of at least one of the first media asset and the second media asset for the first user by comparing the first media asset and the second media asset to the first plurality of media assets; and determine the second context of at least one of the first media asset and the second media asset for the second user by comparing the first media asset and the second media asset to the second plurality of media assets.

7. A system, comprising: a computer-readable storage device configured to receive a plurality of documents received in a continuous stream; and a plurality of network devices, at least one of the plurality of network devices is configured to receive the plurality of documents and to partition the documents for distribution to each of the other network devices based on maximizing a determined dissimilarity of content for documents distributed to each given network device, the dissimilarity being between the documents within a given network device, each network device operable to receive at least some of the plurality of documents, and to perform actions, comprising: applying to at least some of the plurality of documents a modified sequitur algorithm to identify a plurality of common phrases, wherein modifications to the modified sequitur algorithm include using an array instead of a doubly-linked list to represent text, marking a diagram using an indexed array to indicate which position in an original sequence of characters is a start or an end of a non-terminal rule, rather than physically replacing the diagram with a non-terminal rule, and encoding frequent phrases or rules as state machines wherein the state machines are used to chain the identified rules for the identified phrases; selecting from the identified plurality of common phrases at least one phrase as a trending topic phrase for at least a given time window; generating at least one link to at least one of the plurality of documents have content associated with the trending topic phrase; and displaying the trending topic phrase and the at least one link.

7. A system, comprising: a computer-readable storage device configured to receive a plurality of documents received in a continuous stream; and a plurality of network devices, at least one of the plurality of network devices is configured to receive the plurality of documents and to partition the documents for distribution to each of the other network devices based on maximizing a determined dissimilarity of content for documents distributed to each given network device, the dissimilarity being between the documents within a given network device, each network device operable to receive at least some of the plurality of documents, and to perform actions, comprising: applying to at least some of the plurality of documents a modified sequitur algorithm to identify a plurality of common phrases, wherein modifications to the modified sequitur algorithm include using an array instead of a doubly-linked list to represent text, marking a diagram using an indexed array to indicate which position in an original sequence of characters is a start or an end of a non-terminal rule, rather than physically replacing the diagram with a non-terminal rule, and encoding frequent phrases or rules as state machines wherein the state machines are used to chain the identified rules for the identified phrases; selecting from the identified plurality of common phrases at least one phrase as a trending topic phrase for at least a given time window; generating at least one link to at least one of the plurality of documents have content associated with the trending topic phrase; and displaying the trending topic phrase and the at least one link. 10. The system of claim 7 , wherein selecting from the identified plurality of common phrases, further comprises: removing any phrases from the identified plurality of common phrases that is determined to have an extraneous co-occurrence of terms within the phrase based on a t-test test analysis.

1. A method comprising: receiving, within an electronic system including a processor, a user selection of a portal visitor type to create a customizable portal associated with a business organization, wherein the portal visitor type identifies users that can access the customizable portal, wherein the portal visitor type is associated with a department of the business organization; determining content associated with an industry type, wherein the industry type is associated with the portal visitor type and with the department of the business organization; providing the determined content for user selection thereof; and creating the customizable portal configured to be packaged, wherein the customizable portal is based on the selected content, the portal visitor type, the department of the business organization and the industry type, and wherein the customizable portal is configured for automatic archiving based on a group consisting of an expiration date and a content usage threshold associated with the department.

1. A method comprising: receiving, within an electronic system including a processor, a user selection of a portal visitor type to create a customizable portal associated with a business organization, wherein the portal visitor type identifies users that can access the customizable portal, wherein the portal visitor type is associated with a department of the business organization; determining content associated with an industry type, wherein the industry type is associated with the portal visitor type and with the department of the business organization; providing the determined content for user selection thereof; and creating the customizable portal configured to be packaged, wherein the customizable portal is based on the selected content, the portal visitor type, the department of the business organization and the industry type, and wherein the customizable portal is configured for automatic archiving based on a group consisting of an expiration date and a content usage threshold associated with the department. 6. The method of claim 1 further comprising: customizing analytic reports to generate real-time analytic reports regarding user interactions with the customizable portal.

16. A method to marshal and unmarshal data between an extensible markup language (XML) and an object-oriented programming language, comprising: defining an XML data using an XML schema; generating, via a compiler running on one or more processors, an object-oriented programming language type from the XML schema, wherein the object-oriented programming language type is automatically generated for an object-oriented programming language component as an inner class to an XML control interface for the object-oriented programming language component, wherein the object-oriented programming language type corresponds to the XML schema and provides XML-oriented data manipulation, wherein the object-oriented programming language type extends from a base type that allows the combination of XML and object-oriented programming language type systems and can access and manipulate the XML data from within the object-oriented programming language type system; and executing, via the object-oriented programming language type, one or more XML data operations provided by the XML type system, on the XML data, to generate one or more result sets in the object-oriented programming language type system, wherein each of the one or more XML data operations is one of an XML data query operation; an XML data transformation operation; and an XML data iteration operation.

16. A method to marshal and unmarshal data between an extensible markup language (XML) and an object-oriented programming language, comprising: defining an XML data using an XML schema; generating, via a compiler running on one or more processors, an object-oriented programming language type from the XML schema, wherein the object-oriented programming language type is automatically generated for an object-oriented programming language component as an inner class to an XML control interface for the object-oriented programming language component, wherein the object-oriented programming language type corresponds to the XML schema and provides XML-oriented data manipulation, wherein the object-oriented programming language type extends from a base type that allows the combination of XML and object-oriented programming language type systems and can access and manipulate the XML data from within the object-oriented programming language type system; and executing, via the object-oriented programming language type, one or more XML data operations provided by the XML type system, on the XML data, to generate one or more result sets in the object-oriented programming language type system, wherein each of the one or more XML data operations is one of an XML data query operation; an XML data transformation operation; and an XML data iteration operation. 24. The method according to claim 16 , further comprising: accessing and updating object-oriented programming language data using object-oriented programming language type methods.

1. A method comprising: detecting, at a computing device comprising a processor, a frequency of occurrence of a particular type of utterance; determining, using interpretation labels previously assigned to utterances of the particular type of utterance, an accuracy value for the particular type of utterance indicating whether a speech recognition system is correctly interpreting the particular type of utterance, the accuracy value including a false alarm value for the particular type of utterance; and determining, at the computing device, whether to tune the speech recognition system with respect to the particular type of utterance based on the frequency and based on the accuracy value for the particular type of utterance.

1. A method comprising: detecting, at a computing device comprising a processor, a frequency of occurrence of a particular type of utterance; determining, using interpretation labels previously assigned to utterances of the particular type of utterance, an accuracy value for the particular type of utterance indicating whether a speech recognition system is correctly interpreting the particular type of utterance, the accuracy value including a false alarm value for the particular type of utterance; and determining, at the computing device, whether to tune the speech recognition system with respect to the particular type of utterance based on the frequency and based on the accuracy value for the particular type of utterance. 4. The method of claim 1 , wherein the particular type of utterance is an action request.

23. A system for knowledge discovery from a set of free-text documents, the system comprising: means for extracting semi-structured meta-data from the set of free-text documents; means for filtering the semi-structured meta-data to identify a set of key concepts and a corresponding set of key relations between the key concepts, the set of key concepts corresponding to the plurality of concepts; means for deriving at least one set of sub-concepts corresponding to the set of key concepts based upon data within a domain knowledge base, means for formulating training samples, each training sample including a vector representing a sub-concept and a vector representing a key concept; and means for deriving a set of associations between a set of vectors representing a sub-concept and at least one vector representing a key concept, wherein neither the set of text documents nor the semi-structured meta-data mention the set of associations, and wherein the set of associations corresponds to discovered knowledge that is extractable by a knowledge interpreter.

23. A system for knowledge discovery from a set of free-text documents, the system comprising: means for extracting semi-structured meta-data from the set of free-text documents; means for filtering the semi-structured meta-data to identify a set of key concepts and a corresponding set of key relations between the key concepts, the set of key concepts corresponding to the plurality of concepts; means for deriving at least one set of sub-concepts corresponding to the set of key concepts based upon data within a domain knowledge base, means for formulating training samples, each training sample including a vector representing a sub-concept and a vector representing a key concept; and means for deriving a set of associations between a set of vectors representing a sub-concept and at least one vector representing a key concept, wherein neither the set of text documents nor the semi-structured meta-data mention the set of associations, and wherein the set of associations corresponds to discovered knowledge that is extractable by a knowledge interpreter. 25. The system according to claim 23 wherein the semi-structured meta-data is stored in at least one of a permanent and temporary storage.

18. A computer system for facilitating fair scheduling of interests in a content centric network, the system comprising: a processor; and a storage device storing instructions that when executed by the processor cause the processor to perform a method, the method comprising: receiving an initial interest which indicates an allocation of a predetermined number of tokens based on a name prefix and a priority or a weight assigned to a transport stack; receiving a first interest which indicates a command to set a window size for the transport stack based on the name prefix, wherein a name for an interest is a hierarchically structured variable length identifier that includes contiguous name components ordered from a most general level to a most specific level, and wherein a name prefix includes one or more contiguous name components; receiving a second interest with a name that includes the name prefix indicated in the first interest; in response to determining that the window size for the transport stack is sufficient, transmitting the second interest to a forwarder component associated with the transport stack; and in response to determining that the window size is not sufficient, refraining from transmitting the second interest, thereby facilitating scheduling of interests.

18. A computer system for facilitating fair scheduling of interests in a content centric network, the system comprising: a processor; and a storage device storing instructions that when executed by the processor cause the processor to perform a method, the method comprising: receiving an initial interest which indicates an allocation of a predetermined number of tokens based on a name prefix and a priority or a weight assigned to a transport stack; receiving a first interest which indicates a command to set a window size for the transport stack based on the name prefix, wherein a name for an interest is a hierarchically structured variable length identifier that includes contiguous name components ordered from a most general level to a most specific level, and wherein a name prefix includes one or more contiguous name components; receiving a second interest with a name that includes the name prefix indicated in the first interest; in response to determining that the window size for the transport stack is sufficient, transmitting the second interest to a forwarder component associated with the transport stack; and in response to determining that the window size is not sufficient, refraining from transmitting the second interest, thereby facilitating scheduling of interests. 19. The computer system of claim 18 , wherein a respective token is used to forward the second interest with the name that includes the name prefix, wherein: transmitting the second interest to the forwarder component includes transmitting the second interest to the forwarder component in response to determining a sufficient number of tokens for the name prefix refraining from transmitting the second interest includes refraining from transmitting the second interest in response to determining an insufficient number of tokens for the name prefix, the method further comprising: decreasing the number of tokens for the name prefix in response to determining the sufficient number of tokens.

16. A computer readable memory excluding signals tangibly encoded with a computer program executable by a processor to perform actions comprising: loading a first ontology associated with a first rule set, where an ontology is a formal representation of a set of concepts within a domain, and a set of relationships between the concepts; generating an extended ontology and an extended rule set based at least in part on the first ontology and the first rule set; applying the extended rule set to the extended ontology; determining a correctness of the extended ontology, where the correctness is a weighted measurement of errors of the ontology and where the correctness is weighted based at least in part on a type of the errors; and generating results comprising the correctness of the extended ontology.

16. A computer readable memory excluding signals tangibly encoded with a computer program executable by a processor to perform actions comprising: loading a first ontology associated with a first rule set, where an ontology is a formal representation of a set of concepts within a domain, and a set of relationships between the concepts; generating an extended ontology and an extended rule set based at least in part on the first ontology and the first rule set; applying the extended rule set to the extended ontology; determining a correctness of the extended ontology, where the correctness is a weighted measurement of errors of the ontology and where the correctness is weighted based at least in part on a type of the errors; and generating results comprising the correctness of the extended ontology. 20. The computer readable memory of claim 16 , where the first rule set is configured in accordance with a sematic web rule language.

7. A non-transitory computer-readable storage medium, having instructions stored therein, which when executed, cause a computer system to perform operations comprising: receiving at least a first search string and a second search string, where a first length of the first search string is different than a second length of the second search string; and constructing, by a computer system, a matching string machine comprising a plurality of states, wherein the constructing comprises: processing the first search string and the second search string with a tail-first search, associating an initial state of the matching string machine with a pattern, putting each possible character into a point in the pattern, matching each possible character against the first search string and the second search string to identify a match point, and generating a state of the matching string machine in view of the match point; wherein each of the plurality of states has a respective set of state transitions, and wherein each of the respective set of state transitions specifies a shift and a next state that are based on the first length, the second length, and characters of the first search string and the second search string, and wherein at least one of the plurality of states is an accepting state.

7. A non-transitory computer-readable storage medium, having instructions stored therein, which when executed, cause a computer system to perform operations comprising: receiving at least a first search string and a second search string, where a first length of the first search string is different than a second length of the second search string; and constructing, by a computer system, a matching string machine comprising a plurality of states, wherein the constructing comprises: processing the first search string and the second search string with a tail-first search, associating an initial state of the matching string machine with a pattern, putting each possible character into a point in the pattern, matching each possible character against the first search string and the second search string to identify a match point, and generating a state of the matching string machine in view of the match point; wherein each of the plurality of states has a respective set of state transitions, and wherein each of the respective set of state transitions specifies a shift and a next state that are based on the first length, the second length, and characters of the first search string and the second search string, and wherein at least one of the plurality of states is an accepting state. 11. The non-transitory computer-readable storage medium of claim 7 , wherein the constructing of the matching string machine further comprises: forming a first accepting state for the first search string and a second accepting state for the second search string.

13. The computer-implemented method of claim 6 , further comprising determining a level of compression to apply to the portion based at least in part on a linguistic feature of a text corresponding to the portion.

13. The computer-implemented method of claim 6 , further comprising determining a level of compression to apply to the portion based at least in part on a linguistic feature of a text corresponding to the portion. 14. The computer-implemented method of claim 13 , wherein the linguistic feature comprises an identification of a phoneme.

1. A scenario generating apparatus that automatically generates a scenario for animation from an input sentence, the scenario generating apparatus comprising: an input for entering the input sentence into the scenario generating apparatus; an input sentence analyzer that analyzes a meaning of a word written in the input sentence and to which category the word corresponds; a scenario generator that generates a scenario using the analysis result of the input sentence analyzer; a scenario editor that edits the scenario generated by the scenario generator using information anticipated from a term in the scenario, wherein the anticipated information is acquired from the term in the scenario using external information associating the term with the information anticipated from the term; an external information acquiring knowledge storage that stores external information acquiring knowledge, comprising a combination of a type of the external information and acquiring source information relating to an acquiring source of the external information, wherein the external information is acquired using the external information acquiring knowledge stored in the external information acquiring knowledge storage; and a communicator, connected to a network, for controlling network communication with the scenario generating apparatus.

1. A scenario generating apparatus that automatically generates a scenario for animation from an input sentence, the scenario generating apparatus comprising: an input for entering the input sentence into the scenario generating apparatus; an input sentence analyzer that analyzes a meaning of a word written in the input sentence and to which category the word corresponds; a scenario generator that generates a scenario using the analysis result of the input sentence analyzer; a scenario editor that edits the scenario generated by the scenario generator using information anticipated from a term in the scenario, wherein the anticipated information is acquired from the term in the scenario using external information associating the term with the information anticipated from the term; an external information acquiring knowledge storage that stores external information acquiring knowledge, comprising a combination of a type of the external information and acquiring source information relating to an acquiring source of the external information, wherein the external information is acquired using the external information acquiring knowledge stored in the external information acquiring knowledge storage; and a communicator, connected to a network, for controlling network communication with the scenario generating apparatus. 2. The scenario generating apparatus according to claim 1 , wherein the external information is accumulated in at least one of an external information accumulating section provided in the scenario generating apparatus and an external information accumulating apparatus provided outside the scenario generating apparatus, and the external information is acquired from at least one of the external information accumulating section and the external information accumulating apparatus.

12. The method of claim 11 , where the glossary includes an activatable element indicating whether the document structure instance must satisfy the attribute requirement.

12. The method of claim 11 , where the glossary includes an activatable element indicating whether the document structure instance must satisfy the attribute requirement. 13. The method of claim 12 , where the activatable element comprises a selectable icon that controls when to determine whether the attribute requirement is to be satisfied.

24. A method for multimedia scripting in a computer system, comprising the steps of: presenting a script, written in a scripting language, comprising a variable representing one or more multimedia items and a manipulation to be applied to the one or more multimedia items, wherein the scripting language comprises syntax enabling system-wide application of the manipulation; evaluating the script after extraction from a container file at runtime via an interface to one or more programmable processing units communicatively coupled to each other in the computer system; invoking a plurality of processes for manipulating multimedia items in dependence upon the script, each such process associated with one or more multimedia types; processing a first multimedia type with a first process; and processing a second multimedia type with a second process, wherein the script is referenced to render one or more result multimedia items, and is referenced as one or more second original multimedia items in at least one other script for batch manipulation.

24. A method for multimedia scripting in a computer system, comprising the steps of: presenting a script, written in a scripting language, comprising a variable representing one or more multimedia items and a manipulation to be applied to the one or more multimedia items, wherein the scripting language comprises syntax enabling system-wide application of the manipulation; evaluating the script after extraction from a container file at runtime via an interface to one or more programmable processing units communicatively coupled to each other in the computer system; invoking a plurality of processes for manipulating multimedia items in dependence upon the script, each such process associated with one or more multimedia types; processing a first multimedia type with a first process; and processing a second multimedia type with a second process, wherein the script is referenced to render one or more result multimedia items, and is referenced as one or more second original multimedia items in at least one other script for batch manipulation. 32. The method of claim 24 , wherein the process for manipulating multimedia items further comprises the steps of: a first process requesting a filter from a second process; said first process defining a relationship between said filter and said multimedia item, said related filter and multimedia item comprising a program, said second process compiling said program, yielding a compiled program; and running at least a portion of said compiled program to apply a function of said filter to said multimedia item.

1. A method for improving the usability of product feedback data comprising: receiving of a plurality of product feedback search parameters by an intelligent product feedback analytics tool, wherein said plurality of product feedback search parameters pertain to at least one of a product and a group of products; performing a search on plurality of product feedback data sources using the product feedback search parameters to gather product feedback; obtaining a plurality of product feedback search results applicable to the plurality of product feedback search parameters, wherein each product feedback search result comprises at least one of a rating value upon a rating scale and feedback content in a textual format; for each product represented in the obtained plurality of product feedback search results, synthesizing a composite rating value for each rating category of the rating scale defined for the intelligent product feedback analytics tool from rating values contained in product feedback search results that are applicable to the product, wherein the synthesizing comprises: converting the rating value for each product feedback search result to an equivalent rating value with respect to the rating scale defined for the intelligent product feedback analytics tool; assigning each product feedback search result to a rating category of the rating scale defined for the intelligent product feedback analytics tool, wherein the converted rating value of a product feedback search result falls within a rating value range defined for the rating category to which it is assigned; and expressing a quantity of product feedback search results assigned to each rating category as a percentage of a total quantity of product feedback search results that are applicable to the product; for each product represented in the obtained plurality of product feedback search results, analyzing the plurality of product feedback search results for at least one analytic parameter, wherein each analytic parameter represents a commonality among a subset of the product feedback search results that are applicable to the product, wherein said analysis utilizes natural language processing techniques; and presenting the plurality of product feedback search results, composite rating values, and the at least one analytic parameter in an organized manner within a user interface, wherein the at least one analytic parameter presented provides a context for the corresponding composite rating value.

1. A method for improving the usability of product feedback data comprising: receiving of a plurality of product feedback search parameters by an intelligent product feedback analytics tool, wherein said plurality of product feedback search parameters pertain to at least one of a product and a group of products; performing a search on plurality of product feedback data sources using the product feedback search parameters to gather product feedback; obtaining a plurality of product feedback search results applicable to the plurality of product feedback search parameters, wherein each product feedback search result comprises at least one of a rating value upon a rating scale and feedback content in a textual format; for each product represented in the obtained plurality of product feedback search results, synthesizing a composite rating value for each rating category of the rating scale defined for the intelligent product feedback analytics tool from rating values contained in product feedback search results that are applicable to the product, wherein the synthesizing comprises: converting the rating value for each product feedback search result to an equivalent rating value with respect to the rating scale defined for the intelligent product feedback analytics tool; assigning each product feedback search result to a rating category of the rating scale defined for the intelligent product feedback analytics tool, wherein the converted rating value of a product feedback search result falls within a rating value range defined for the rating category to which it is assigned; and expressing a quantity of product feedback search results assigned to each rating category as a percentage of a total quantity of product feedback search results that are applicable to the product; for each product represented in the obtained plurality of product feedback search results, analyzing the plurality of product feedback search results for at least one analytic parameter, wherein each analytic parameter represents a commonality among a subset of the product feedback search results that are applicable to the product, wherein said analysis utilizes natural language processing techniques; and presenting the plurality of product feedback search results, composite rating values, and the at least one analytic parameter in an organized manner within a user interface, wherein the at least one analytic parameter presented provides a context for the corresponding composite rating value. 2. The method of claim 1 , comprising: querying an analytic search results library for entries matching the received plurality of product feedback search parameters, wherein the analytic search results library is a knowledgebase of product feedback search results previously processed by the intelligent product feedback analytics tool; when matching entries are absent from the analytic search results library, requesting the plurality of product feedback search results for the plurality of product feedback search parameters from a content aggregator, wherein said content aggregator is capable of accessing data sources required by the intelligent product feedback analytics tool; and receiving the plurality of product feedback search results from the content aggregator.

1. A method for career matching assessment, comprising: accessing on an application on a target network device with one or more processors from a server network device with one or more processors via a communications network, one or more electronic questionnaires created for a selected job opening for a first job seeker, the one or more electronic questionnaires including: (1) a plurality of non-self assessment questions for the first job seeker that are answered by the seekers as if the first job seeker were actually an employer offering the selected job opening instead of the job seeker seeking the selected job opening and (2) a plurality of general questions that focus on different aspects of a working environment and working relationships and do not access any underlying personality traits of the first job seekers; sending the one or more electronic questionnaires completed on the application on the target network device for the first job seeker to the server network device via the communications network for the selected job opening; processing the completed one or more electronic questionnaires from first job seeker on the server network device to create a first electronic profile for the first job seeker, wherein the created first electronic profile measures attributes of models of working environments, problem solving, communication and inter-personal skills related to job performance and job satisfaction for the first job seeker for the selected job opening; invoking a matching process to assess an amount of overlap between the created first electronic profile for the first job seeker and a plurality of other electronic profiles of created by a plurality of other job seekers and the employer profile created by an employer for the selected job opening; creating an electronic priority list from the assessed amount of overlap to list job seeker candidates in rank order for the selected job opening most desirable to the employer, wherein the priority list includes a prediction of job performance, job satisfaction and long term job retention for the job seeker candidates for the selected job opening for the employer; sending an automatic notification from the server network device to the application on the target network device via the communications network to indicate a priority ranking for the selected job opening for the job seeker; and displaying with the application on the target network device the automatic notification to indicate a priority ranking for the selected job opening for the job seeker.

1. A method for career matching assessment, comprising: accessing on an application on a target network device with one or more processors from a server network device with one or more processors via a communications network, one or more electronic questionnaires created for a selected job opening for a first job seeker, the one or more electronic questionnaires including: (1) a plurality of non-self assessment questions for the first job seeker that are answered by the seekers as if the first job seeker were actually an employer offering the selected job opening instead of the job seeker seeking the selected job opening and (2) a plurality of general questions that focus on different aspects of a working environment and working relationships and do not access any underlying personality traits of the first job seekers; sending the one or more electronic questionnaires completed on the application on the target network device for the first job seeker to the server network device via the communications network for the selected job opening; processing the completed one or more electronic questionnaires from first job seeker on the server network device to create a first electronic profile for the first job seeker, wherein the created first electronic profile measures attributes of models of working environments, problem solving, communication and inter-personal skills related to job performance and job satisfaction for the first job seeker for the selected job opening; invoking a matching process to assess an amount of overlap between the created first electronic profile for the first job seeker and a plurality of other electronic profiles of created by a plurality of other job seekers and the employer profile created by an employer for the selected job opening; creating an electronic priority list from the assessed amount of overlap to list job seeker candidates in rank order for the selected job opening most desirable to the employer, wherein the priority list includes a prediction of job performance, job satisfaction and long term job retention for the job seeker candidates for the selected job opening for the employer; sending an automatic notification from the server network device to the application on the target network device via the communications network to indicate a priority ranking for the selected job opening for the job seeker; and displaying with the application on the target network device the automatic notification to indicate a priority ranking for the selected job opening for the job seeker. 2. The method of claim 1 wherein the one or more electronic questionnaires include a plurality of Hyper Text Markup Language (HTML) forms, Extensible Markup Language (XML) forms or Java forms.

8. A non-transitory computer readable storage device comprising a resource management software module that is operative, when executed by a processor, to perform a method, the method comprising: defining a plurality of translating references for an object; generating a common information model (CIM), the CIM comprising one or more functional object attributes of the object; generating a first instantiation of a user information model (UIM), the first instantiation of the UIM comprising one or more user-associated attributes of the object; interfacing with the CIM using the first instantiation of the UIM; translating one or more user-associated attributes of the first instantiation of the UIM to the one or more functional object attributes of the CIM using the plurality of translating references; generating a second instantiation of a user information model (UIM); interfacing with the CIM using the second instantiation of the UIM; translating one or more user-associated attributes of the second instantiation of the UIM to the one or more functional object attributes of the CIM using the plurality of translating references; and providing at least a portion of the CIM.

8. A non-transitory computer readable storage device comprising a resource management software module that is operative, when executed by a processor, to perform a method, the method comprising: defining a plurality of translating references for an object; generating a common information model (CIM), the CIM comprising one or more functional object attributes of the object; generating a first instantiation of a user information model (UIM), the first instantiation of the UIM comprising one or more user-associated attributes of the object; interfacing with the CIM using the first instantiation of the UIM; translating one or more user-associated attributes of the first instantiation of the UIM to the one or more functional object attributes of the CIM using the plurality of translating references; generating a second instantiation of a user information model (UIM); interfacing with the CIM using the second instantiation of the UIM; translating one or more user-associated attributes of the second instantiation of the UIM to the one or more functional object attributes of the CIM using the plurality of translating references; and providing at least a portion of the CIM. 9. The computer readable storage device of claim 8 , wherein the first instantiation of the UIM is a service management model and the second instantiation of the UIM is a transport resources management model.

1. A computer implemented method of identifying parallel bilingual corpora from one or more larger corpora accessible over a network using a computer with a processor, comprising: accessing a given website; identifying specific trigger words in text of hyperlinks on pages of the given website that link to other pages; selecting a first subset of data in a first language and a second subset of data in a second language from the other pages linked to by the hyperlinks that have the specific trigger words; verifying sufficient parallelism between the first and second subsets of the data based on a plurality of features of the first and second subsets of data, the features being indicative of whether the second subset of data is a translation of the first subset of data; if the first and second subsets of data are sufficiently parallel, obtaining, with the processor, a first tree structure corresponding to the first subset of data and a second tree structure corresponding to the second subset of data, each tree structure having hierarchically and sequentially arranged nodes comprising hyperlink tags and text nodes representing hyperlinks and text in the corresponding subset of data; aligning, with the processor, the tree structures corresponding to each of the subsets of data according to a hierarchically and sequentially invariant alignment such that when a first node in the first tree structure is aligned with a second node in the second tree structure, then nodes that descend from the second node in the second tree structure are either deleted or aligned with nodes that descend from the first node in the first tree structure and nodes that descend from the first node in the first tree structure are either deleted or aligned with nodes that descend from the second node in the second tree structure; identifying parallel textual segments of the subsets of data based on the alignment of the tree structures; and outputting an indication of the parallel textual segments.

1. A computer implemented method of identifying parallel bilingual corpora from one or more larger corpora accessible over a network using a computer with a processor, comprising: accessing a given website; identifying specific trigger words in text of hyperlinks on pages of the given website that link to other pages; selecting a first subset of data in a first language and a second subset of data in a second language from the other pages linked to by the hyperlinks that have the specific trigger words; verifying sufficient parallelism between the first and second subsets of the data based on a plurality of features of the first and second subsets of data, the features being indicative of whether the second subset of data is a translation of the first subset of data; if the first and second subsets of data are sufficiently parallel, obtaining, with the processor, a first tree structure corresponding to the first subset of data and a second tree structure corresponding to the second subset of data, each tree structure having hierarchically and sequentially arranged nodes comprising hyperlink tags and text nodes representing hyperlinks and text in the corresponding subset of data; aligning, with the processor, the tree structures corresponding to each of the subsets of data according to a hierarchically and sequentially invariant alignment such that when a first node in the first tree structure is aligned with a second node in the second tree structure, then nodes that descend from the second node in the second tree structure are either deleted or aligned with nodes that descend from the first node in the first tree structure and nodes that descend from the first node in the first tree structure are either deleted or aligned with nodes that descend from the second node in the second tree structure; identifying parallel textual segments of the subsets of data based on the alignment of the tree structures; and outputting an indication of the parallel textual segments. 2. The method of claim 1 wherein the first and second subsets of data comprise first and second pages having hyperlinks to other documents, and further comprising: identifying parallel hyperlinks in the first and second documents based on the alignment of the tree structures, the parallel hyperlinks linking to a subsequent document in the first language and a subsequent document in the second language, respectively.

15. A process for preparing an architectural specification comprising: storing recorded signals representative of instruction data on an instruction data file; storing recorded signals representative of a plurality of phrases with associated code on a specification data file; whereby a specifier by writing code may determine the sequence and relation of said phrases; programming a data processor to receive input code representative of a predetermined sequence of said phrases and to check said input code to determine whether it contains any errors which would prevent further processing of said input code and, if not, to prepare an edited input file of said code; programming said processor to process the code on said edited input file and to prepare a printed specification from said specification data file according to the code sequenced by a specifier and to prepare a set of signals on an instruction input file, said last-named signals being correlated with said phrases through said input code; and programming said data processor to operate on said instruction input file to prepare a set of instructions from said instruction data file; said instructions being associated with corresponding data on said printed specification.

15. A process for preparing an architectural specification comprising: storing recorded signals representative of instruction data on an instruction data file; storing recorded signals representative of a plurality of phrases with associated code on a specification data file; whereby a specifier by writing code may determine the sequence and relation of said phrases; programming a data processor to receive input code representative of a predetermined sequence of said phrases and to check said input code to determine whether it contains any errors which would prevent further processing of said input code and, if not, to prepare an edited input file of said code; programming said processor to process the code on said edited input file and to prepare a printed specification from said specification data file according to the code sequenced by a specifier and to prepare a set of signals on an instruction input file, said last-named signals being correlated with said phrases through said input code; and programming said data processor to operate on said instruction input file to prepare a set of instructions from said instruction data file; said instructions being associated with corresponding data on said printed specification. 16. The process of claim 15 further comprising the step of programming said data processor to prepare a table of contents including major subheadings of said printed specification and a table of non-fatal errors contained in said input code.

8. The apparatus of claim 6 , wherein the single image recognition technique comprises an image recognition algorithm to be applied to the input image with use of one of the image recognition dictionaries.

8. The apparatus of claim 6 , wherein the single image recognition technique comprises an image recognition algorithm to be applied to the input image with use of one of the image recognition dictionaries. 9. The apparatus of claim 8 , wherein the single image recognition technique further comprises image correction applied to the input image prior to application of the image recognition algorithm to the input image.

2. The system in accordance with claim 1 , further comprising broadcast settings, wherein the broadcast settings comprise one or more user-defined settings for the one or more receivers.

2. The system in accordance with claim 1 , further comprising broadcast settings, wherein the broadcast settings comprise one or more user-defined settings for the one or more receivers. 4. The system in accordance with claim 2 , wherein the user-defined settings comprise one or more parameters to specify how a receiver prefers to receive the document, and wherein the one or more user settings comprise a type of data included in the document and a document template.

1. A method, performed on a server, which is part of a process for translating between languages, the method comprising: receiving first audio data in a first language from a mobile device; identifying the first language: receiving second audio data in a second language from the mobile device: identifying the second language: receiving an indication that the mobile device has moved between two users, wherein movement of mobile device comprises at least moving the mobile device angularly relative to a predefined reference; and in response to the indication that the mobile device has moved: sending, to the mobile device, translation data that corresponds to audio data translated from one language into another language; wherein, in a case that the mobile device has moved from a first location to a second location, the translation data corresponds to received audio data translated into the second language and, in a case that the mobile device has moved from the second location to the first location, the translation data corresponds to the received audio data translated into the first language: and wherein subsequent operations of the server for translating between the first language and the second language are triggered automatically by subsequent indications that the mobile device has moved.

1. A method, performed on a server, which is part of a process for translating between languages, the method comprising: receiving first audio data in a first language from a mobile device; identifying the first language: receiving second audio data in a second language from the mobile device: identifying the second language: receiving an indication that the mobile device has moved between two users, wherein movement of mobile device comprises at least moving the mobile device angularly relative to a predefined reference; and in response to the indication that the mobile device has moved: sending, to the mobile device, translation data that corresponds to audio data translated from one language into another language; wherein, in a case that the mobile device has moved from a first location to a second location, the translation data corresponds to received audio data translated into the second language and, in a case that the mobile device has moved from the second location to the first location, the translation data corresponds to the received audio data translated into the first language: and wherein subsequent operations of the server for translating between the first language and the second language are triggered automatically by subsequent indications that the mobile device has moved. 5. The method of claim 1 , wherein identifying at least one of the first language or the second language comprises: providing language options to the mobile device; receiving one or more selections from among the language options; and designating one or more of the first language and the second language based on the one or more selections.

16. A non-transitory volatile or non-volatile machine-readable storage medium storing one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform: converting an instance of a complex type from (a) a first storage format within a first database used at a source site to store the instance of the complex type to (b) a logical representation that conforms to a markup language and is recognized among multiple sites; propagating said logical representation to at least one destination site; and at a destination site, converting said logical representation to a second storage format used to store instances of the complex type within a second database at the destination site, said second storage format different from said first storage format; wherein the instance of the complex type in the first storage format within the first database at the source site includes an object identifier that identifies at least part of the instance of the complex type at the source site, wherein the object identifier is tied to the source site and is not used to identify the at least part of the instance of the complex type in the second storage format within the second database at the destination site, and wherein the logical representation includes a globally unique identifier that is recognized among the multiple sites as representing the at least part of the instance of the complex type.

16. A non-transitory volatile or non-volatile machine-readable storage medium storing one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform: converting an instance of a complex type from (a) a first storage format within a first database used at a source site to store the instance of the complex type to (b) a logical representation that conforms to a markup language and is recognized among multiple sites; propagating said logical representation to at least one destination site; and at a destination site, converting said logical representation to a second storage format used to store instances of the complex type within a second database at the destination site, said second storage format different from said first storage format; wherein the instance of the complex type in the first storage format within the first database at the source site includes an object identifier that identifies at least part of the instance of the complex type at the source site, wherein the object identifier is tied to the source site and is not used to identify the at least part of the instance of the complex type in the second storage format within the second database at the destination site, and wherein the logical representation includes a globally unique identifier that is recognized among the multiple sites as representing the at least part of the instance of the complex type. 17. The volatile or non-volatile machine-readable storage medium of claim 16 , wherein one or more sequences of instructions causes the one or more processors to perform converting the instance by incorporating within said logical representation information that identifies the type of the complex type.

8. The method of claim 1 , wherein said determining comprises using a conditional random field-based technique, wherein a conditional random field is trained to model at least one confusion and account for at least one error in a phonetic decoding derived from an automatic speech recognition output.

8. The method of claim 1 , wherein said determining comprises using a conditional random field-based technique, wherein a conditional random field is trained to model at least one confusion and account for at least one error in a phonetic decoding derived from an automatic speech recognition output. 9. The method of claim 8 , wherein training data for the conditional random field comprises at least one pair of input and output phone sequences corresponding to a reference phone sequence and a decoded phone sequence, respectively.

10. An apparatus comprising: at least one storage device storing instructions; and a processor to execute the instructions to: receive a corpus of textual listings, textual listings, in the corpus, including one or more advertisements, the one or more advertisements including text without a grammatical structure; identify main concept words and attribute words in the corpus, when identifying the main concept words and the attribute words, the processor is to: tag, in each textual listing of the textual listings, at least one word as a head noun word based on at least one of: a previously identified main concept word, or a head noun identification rule, tag, in the textual listing and after tagging the at least one word, remaining nouns as at least one modifier word, and assign one word of the at least one head noun word as a main concept word and one word of the at least one modifier word as an attribute word; cluster words in the corpus based on at least one of the main concept words or the attribute words according to at least one clustering rule, the at least one clustering rule including at least one of: a first rule relating to clustering two quantitative attribute tokens based on a frequency of appearance of the two quantitative attribute tokens in a same listing, a second rule relating to clustering of a quantitative attribute token with a qualitative attribute token, or a third rule relating to clustering a first token and a second token based on characters of the first token being included in the second token; and provide, after clustering the words, the main concept words and the attribute words as at least a portion of a semantic model.

10. An apparatus comprising: at least one storage device storing instructions; and a processor to execute the instructions to: receive a corpus of textual listings, textual listings, in the corpus, including one or more advertisements, the one or more advertisements including text without a grammatical structure; identify main concept words and attribute words in the corpus, when identifying the main concept words and the attribute words, the processor is to: tag, in each textual listing of the textual listings, at least one word as a head noun word based on at least one of: a previously identified main concept word, or a head noun identification rule, tag, in the textual listing and after tagging the at least one word, remaining nouns as at least one modifier word, and assign one word of the at least one head noun word as a main concept word and one word of the at least one modifier word as an attribute word; cluster words in the corpus based on at least one of the main concept words or the attribute words according to at least one clustering rule, the at least one clustering rule including at least one of: a first rule relating to clustering two quantitative attribute tokens based on a frequency of appearance of the two quantitative attribute tokens in a same listing, a second rule relating to clustering of a quantitative attribute token with a qualitative attribute token, or a third rule relating to clustering a first token and a second token based on characters of the first token being included in the second token; and provide, after clustering the words, the main concept words and the attribute words as at least a portion of a semantic model. 15. The apparatus of claim 10 , where, when assigning the one word of the at least one head noun word as the main concept word, the processor is to: assign the one word, of the at least one head noun word, as the main concept word when a ratio of a frequency of the one word, of the at least one head noun word, being tagged as a head noun word to a frequency of the one word, of the at least one head noun word, being tagged as a modifier word is greater than a main concept threshold.

1. An apparatus, comprising: a logic device; and an information visualization application operative on the logic device, the information visualization application comprising a multivariable presentation component arranged to generate a multivariable decomposition visualization to present hierarchical information for a response variable and multiple reporting variables defined for the response variable in a single user interface view, the multivariable decomposition visualization comprising multiple graphical user interface (GUI) elements each representing a reporting variable value of multiple reporting variables for multiple hierarchical levels, with a GUI element of a reporting variable value of a reporting variable of a hierarchical level selectable for decomposition into multiple GUI elements representing reporting variable values of a different reporting variable for a different hierarchical level, the selectable GUI element of the hierarchical level positioned adjacent to the decomposed GUI elements of the different hierarchical level when the selectable GUI element is selected for decomposition.

1. An apparatus, comprising: a logic device; and an information visualization application operative on the logic device, the information visualization application comprising a multivariable presentation component arranged to generate a multivariable decomposition visualization to present hierarchical information for a response variable and multiple reporting variables defined for the response variable in a single user interface view, the multivariable decomposition visualization comprising multiple graphical user interface (GUI) elements each representing a reporting variable value of multiple reporting variables for multiple hierarchical levels, with a GUI element of a reporting variable value of a reporting variable of a hierarchical level selectable for decomposition into multiple GUI elements representing reporting variable values of a different reporting variable for a different hierarchical level, the selectable GUI element of the hierarchical level positioned adjacent to the decomposed GUI elements of the different hierarchical level when the selectable GUI element is selected for decomposition. 17. The apparatus of claim 1 , the multivariable presentation component operative to receive an aggregation control directive, and aggregate values for a set of reporting variables for the multivariable decomposition visualization in response to the aggregation control directive.

1. A computer program product for identifying universal resource locator rewriting rules, the computer program product comprising: a non-transitory computer readable storage medium including computer executable program code stored thereon, the computer executable program code comprising: computer executable program code for receiving input of universal resource locators of an application, to form received universal resource locators; computer executable program code for representing the received universal resource locators in a graph; computer executable program code for applying analysis algorithms and heuristics to properties of the graph; computer executable program code for identifying universal resource locator rewriting patterns using the graph to form detected patterns, including if a switch has a complexity value greater than a predetermined value “Q”, grouping identified switches into Left Switches and Right Switches according to a connection set; and computer executable program code for generating rewrite rules corresponding to the detected patterns.

1. A computer program product for identifying universal resource locator rewriting rules, the computer program product comprising: a non-transitory computer readable storage medium including computer executable program code stored thereon, the computer executable program code comprising: computer executable program code for receiving input of universal resource locators of an application, to form received universal resource locators; computer executable program code for representing the received universal resource locators in a graph; computer executable program code for applying analysis algorithms and heuristics to properties of the graph; computer executable program code for identifying universal resource locator rewriting patterns using the graph to form detected patterns, including if a switch has a complexity value greater than a predetermined value “Q”, grouping identified switches into Left Switches and Right Switches according to a connection set; and computer executable program code for generating rewrite rules corresponding to the detected patterns. 5. The computer program product of claim 1 , wherein computer executable program code for identifying universal resource locator rewriting patterns using the graph to form detected patterns further comprises: computer executable program code responsive to determination that more switches that connect do not exist, for applying selected optimization and filters to each element of a rewrite rules collection to create an optimized list.

1. A method comprising: outputting, by a computing device and for display at a display device, a graphical keyboard comprising a plurality of character keys; receiving, at the computing device, an indication of a first input gesture, a first portion of the first input gesture indicating a first character key of the plurality of character keys and a second portion of the first input gesture indicating a second character key of the plurality of character keys; determining, by the computing device and based at least in part on the first character key and the second character key, a candidate word; outputting, by the computing device and for display at a region of the display device at which the graphical keyboard is displayed, a gesture completion path extending from the second character key, the second character key being the most recently indicated character key, and the gesture completion path being associated with the candidate word; and selecting, by the computing device and in response to receiving an indication of a second input gesture that substantially traverses the gesture completion path, the candidate word associated with the gesture completion path.

1. A method comprising: outputting, by a computing device and for display at a display device, a graphical keyboard comprising a plurality of character keys; receiving, at the computing device, an indication of a first input gesture, a first portion of the first input gesture indicating a first character key of the plurality of character keys and a second portion of the first input gesture indicating a second character key of the plurality of character keys; determining, by the computing device and based at least in part on the first character key and the second character key, a candidate word; outputting, by the computing device and for display at a region of the display device at which the graphical keyboard is displayed, a gesture completion path extending from the second character key, the second character key being the most recently indicated character key, and the gesture completion path being associated with the candidate word; and selecting, by the computing device and in response to receiving an indication of a second input gesture that substantially traverses the gesture completion path, the candidate word associated with the gesture completion path. 14. The method of claim 1 , wherein the wherein the graphical keyboard comprises a layout other than a QWERTY layout.

10. A system comprising: a first apparatus comprising a first processor and a second apparatus comprising a second processor; and a computer readable storage medium to store a first application having computer readable program code and a second application having computer readable program code, wherein the first processor executes the computer readable program code of the first application to: create on a server computing device a plurality of executable modules, each executable module comprising a first variable and a flag comprising a first predetermined value if the executable module may be published to a client computing device, and a second predetermined value if the executable module may not be published to the client computing device; create on the server computing device a first template comprising a selection of one of the executable modules comprising the flag comprising the first predetermined value and a specification of the first variable; link the one executable module to the first template; and communicate information about the first template from the server computing device to the client computing device; wherein the second processor executes the computer readable program code of the second application to: receive on the client computing device a selection of the first template; receive on the client computing device a configuration of the specified first variable; and save the selected template and the configured first variable as an application program interface (API) on the server computing device.

10. A system comprising: a first apparatus comprising a first processor and a second apparatus comprising a second processor; and a computer readable storage medium to store a first application having computer readable program code and a second application having computer readable program code, wherein the first processor executes the computer readable program code of the first application to: create on a server computing device a plurality of executable modules, each executable module comprising a first variable and a flag comprising a first predetermined value if the executable module may be published to a client computing device, and a second predetermined value if the executable module may not be published to the client computing device; create on the server computing device a first template comprising a selection of one of the executable modules comprising the flag comprising the first predetermined value and a specification of the first variable; link the one executable module to the first template; and communicate information about the first template from the server computing device to the client computing device; wherein the second processor executes the computer readable program code of the second application to: receive on the client computing device a selection of the first template; receive on the client computing device a configuration of the specified first variable; and save the selected template and the configured first variable as an application program interface (API) on the server computing device. 14. The system of claim 10 , wherein the first apparatus comprises the server computing device, comprising an API gateway.

1. A method for merging taxonomies comprising: initializing a merged taxonomy, by a computer system, by merging at least one node of a plurality of nodes of a second taxonomy to at least one node of a plurality of nodes of a first taxonomy, the merged taxonomy comprising the first taxonomy and the second taxonomy; merging, by the computer system, the second taxonomy into the merged taxonomy by, traversing the second taxonomy from below at least one top level of the second taxonomy toward a bottom of the second taxonomy and performing: comparing, by the computer system, one or more identifiers or titles of the at least one node of the plurality of nodes of the second taxonomy to one or more identifiers or titles of the at least one node of the plurality of nodes of the first taxonomy; comparing, by the computer system, one or more lineages of one or more unmerged nodes of the plurality of nodes of the second taxonomy in the merged taxonomy to one or more lineages of one or more nodes of the plurality of nodes of the first taxonomy; and merging, by the computer system, the at least one node of the plurality of nodes of the second taxonomy and the at least one node of the plurality of nodes of the first taxonomy in the merged taxonomy if the comparison of the one or more identifiers or titles of the at least one node of the plurality of nodes of the second taxonomy to the one or more identifiers or titles of the at least one node of the plurality of nodes of the first taxonomy and the comparison of the one or more lineages of the one or more unmerged nodes of the second taxonomy in the merged taxonomy to the one or more lineages of the one or more nodes of the plurality of nodes of the first taxonomy satisfy a threshold condition; and for each unmerged node of the plurality of nodes of the second taxonomy, hereinafter a current node of the plurality of nodes of the second taxonomy: filtering the plurality of nodes of the first taxonomy according to a Jaccard distance of titles thereof with respect to a title of the current node of the plurality of nodes of the second taxonomy to define a filtered set of nodes; calculating an edit distance between the current node of the plurality of nodes of the second taxonomy and each node of the filtered set of nodes; calculating a lineage score for each node of the filtered set of nodes according to a comparison of a lineage of the current node of the plurality of nodes of the second taxonomy in the merged taxonomy to lineages of nodes of the filtered set of nodes; and merging the current node of the plurality of nodes of the second taxonomy with a selected node of the filtered set of nodes if a combined score of the edit distance and the lineage score for the selected node is both: a greatest combined score for the nodes of the filtered set of nodes; and the combined score for the selected node of the filtered set of nodes satisfies a combined score threshold condition.

1. A method for merging taxonomies comprising: initializing a merged taxonomy, by a computer system, by merging at least one node of a plurality of nodes of a second taxonomy to at least one node of a plurality of nodes of a first taxonomy, the merged taxonomy comprising the first taxonomy and the second taxonomy; merging, by the computer system, the second taxonomy into the merged taxonomy by, traversing the second taxonomy from below at least one top level of the second taxonomy toward a bottom of the second taxonomy and performing: comparing, by the computer system, one or more identifiers or titles of the at least one node of the plurality of nodes of the second taxonomy to one or more identifiers or titles of the at least one node of the plurality of nodes of the first taxonomy; comparing, by the computer system, one or more lineages of one or more unmerged nodes of the plurality of nodes of the second taxonomy in the merged taxonomy to one or more lineages of one or more nodes of the plurality of nodes of the first taxonomy; and merging, by the computer system, the at least one node of the plurality of nodes of the second taxonomy and the at least one node of the plurality of nodes of the first taxonomy in the merged taxonomy if the comparison of the one or more identifiers or titles of the at least one node of the plurality of nodes of the second taxonomy to the one or more identifiers or titles of the at least one node of the plurality of nodes of the first taxonomy and the comparison of the one or more lineages of the one or more unmerged nodes of the second taxonomy in the merged taxonomy to the one or more lineages of the one or more nodes of the plurality of nodes of the first taxonomy satisfy a threshold condition; and for each unmerged node of the plurality of nodes of the second taxonomy, hereinafter a current node of the plurality of nodes of the second taxonomy: filtering the plurality of nodes of the first taxonomy according to a Jaccard distance of titles thereof with respect to a title of the current node of the plurality of nodes of the second taxonomy to define a filtered set of nodes; calculating an edit distance between the current node of the plurality of nodes of the second taxonomy and each node of the filtered set of nodes; calculating a lineage score for each node of the filtered set of nodes according to a comparison of a lineage of the current node of the plurality of nodes of the second taxonomy in the merged taxonomy to lineages of nodes of the filtered set of nodes; and merging the current node of the plurality of nodes of the second taxonomy with a selected node of the filtered set of nodes if a combined score of the edit distance and the lineage score for the selected node is both: a greatest combined score for the nodes of the filtered set of nodes; and the combined score for the selected node of the filtered set of nodes satisfies a combined score threshold condition. 9. The method of claim 1 , wherein: comparing the one or more identifiers or titles of the at least one node of the plurality of nodes of the second taxonomy to the one or more identifiers or titles of the at least one node of the plurality of nodes of the first taxonomy comprises: computing a Jaccard distance, the Jaccard distance is a JaccardScore calculated as: JaccardScore = common_words ⁢ _idf queryidf + conceptidf - common_words ⁢ _idf × common_words ⁢ _idf queryidf i where queryidf and conceptidf are value of idf computed according to idf = ∑ i = 1 n ⁢ ⁢ log ⁢ N docfreq ⁡ ( w i ) + 1 , where w i is a word in an identifier for a node in the second taxonomy for queryidf and an a word in an identifier for a node in the first taxonomy for conceptidf, docfreq(w i ) is a number of times that the word w i , occurs in identifiers of nodes in the first taxonomy, n is a number of words in common in the identifier for the node in the second taxonomy for queryidf and for the node in the first taxonomy for conceptidf, and N is a number of concepts in the first taxonomy and where common_words_idf is a value of idf, and where w i includes common words to both the node in the second taxonomy and the node in the first taxonomy.

9. A system for text driven document sizing for a plurality of differently-sized documents in a rendering device, comprising: a data-processing apparatus; a module executed by said data-processing apparatus, said module and said data-processing apparatus being operable in combination with one another to: automatically detect document sizes for said plurality of differently-sized documents by pre-scanning all sides of said plurality of differently-sized documents to determine said minimum output document sizes needed to accommodate all sides of said plurality of differently-sized documents, wherein reproduced output document sizes of said plurality of differently-sized documents are larger sides of said plurality of differently-sized documents; automatically detect minimum text size of text contained in plurality of differently-sized documents; record said minimum text sizes of said text contained in said plurality of differently-sized documents; detect output document sizes available to said rendering device in response to automatically detecting said minimum text sizes of said text contained in said plurality of differently-sized documents and specifying a particular said minimum set text sizes; utilize said detected said minimum text sizes and said particular minimum set text sizes to automatically determine image magnification ratios and document sizes required to achieve said particular minimum text sizes in rendered documents via said rendering device, wherein text sizes achieved in said rendered documents are as close as possible to said particular minimum set text sizes if said particular minimum set text sizes specified are unachievable; recalculating said magnification ratio to fill a largest loaded paper size; and automatically optimizing said plurality of differently-sized documents reproduction factors including at least one of original document size, image size, magnification ratios, and output document sizes.

9. A system for text driven document sizing for a plurality of differently-sized documents in a rendering device, comprising: a data-processing apparatus; a module executed by said data-processing apparatus, said module and said data-processing apparatus being operable in combination with one another to: automatically detect document sizes for said plurality of differently-sized documents by pre-scanning all sides of said plurality of differently-sized documents to determine said minimum output document sizes needed to accommodate all sides of said plurality of differently-sized documents, wherein reproduced output document sizes of said plurality of differently-sized documents are larger sides of said plurality of differently-sized documents; automatically detect minimum text size of text contained in plurality of differently-sized documents; record said minimum text sizes of said text contained in said plurality of differently-sized documents; detect output document sizes available to said rendering device in response to automatically detecting said minimum text sizes of said text contained in said plurality of differently-sized documents and specifying a particular said minimum set text sizes; utilize said detected said minimum text sizes and said particular minimum set text sizes to automatically determine image magnification ratios and document sizes required to achieve said particular minimum text sizes in rendered documents via said rendering device, wherein text sizes achieved in said rendered documents are as close as possible to said particular minimum set text sizes if said particular minimum set text sizes specified are unachievable; recalculating said magnification ratio to fill a largest loaded paper size; and automatically optimizing said plurality of differently-sized documents reproduction factors including at least one of original document size, image size, magnification ratios, and output document sizes. 12. The system of claim 9 wherein said module and said data-processing apparatus are further operable in combination with one another to manually select text areas within said plurality of differently-sized documents for magnification to a desired text size on a scalable basis as a number of text areas and print jobs increase.

6. A computer implemented system comprising: a memory storing instructions; one or more communication interfaces; one or more hardware processors, coupled to said memory using said one or more interfaces; an identification module coupled to the processor, wherein the identification module is configured to identify a business rule in a text document and token size and tag a candidate rule using part-of-speech (POS) tags, wherein the business rule comprises one or more rule intents; the identification module configured to a rule repository based on an identified business rule and the one or more rule intents, wherein the rule intents are atomic constraints stored in an ontology form a classification module, coupled to the processor, wherein the classification module is configured to: compare, the one or more rule intents in the business rule with the one or more clusters associated with a plurality of rule types in the rule repository to compute a match score, wherein the match score is indicative of the number of rule intents and based on the match score, the business rule is annotated with one or more rule types in the rule repository, and wherein the rule repository is periodically updated with a plurality of new rule intents, said rule intent patterns and new rule types; classify the business rule under at least one rule type, amongst the plurality of rule types, based on the match score to further classify the business rule into at least one of formatted and unformatted text documents for referring and tracing the text document by annotating the business rule with one or more corresponding rule intents and one or more rule types in the rule repository; trigger an annotation module to highlight the business rule in a document and to annotate the business rule with at least one of the one or more rule intents and rule types in the rule repository; cluster the one or more rule intents in an agglomerative manner to identify one or more clustering rule intents that co-occur frequently in the rule repository; assemble the one or more clusters into a plurality of clustering techniques, wherein the rule repository is periodically updated with the corresponding rule intent and the rule type to classify sentences obtained from a training data set; and automatically associate the business rules extracted from the text document with a plurality of corresponding knowledge element types and system components to reference, trace and re-use at least one of requirement artifacts and system documentation.

6. A computer implemented system comprising: a memory storing instructions; one or more communication interfaces; one or more hardware processors, coupled to said memory using said one or more interfaces; an identification module coupled to the processor, wherein the identification module is configured to identify a business rule in a text document and token size and tag a candidate rule using part-of-speech (POS) tags, wherein the business rule comprises one or more rule intents; the identification module configured to a rule repository based on an identified business rule and the one or more rule intents, wherein the rule intents are atomic constraints stored in an ontology form a classification module, coupled to the processor, wherein the classification module is configured to: compare, the one or more rule intents in the business rule with the one or more clusters associated with a plurality of rule types in the rule repository to compute a match score, wherein the match score is indicative of the number of rule intents and based on the match score, the business rule is annotated with one or more rule types in the rule repository, and wherein the rule repository is periodically updated with a plurality of new rule intents, said rule intent patterns and new rule types; classify the business rule under at least one rule type, amongst the plurality of rule types, based on the match score to further classify the business rule into at least one of formatted and unformatted text documents for referring and tracing the text document by annotating the business rule with one or more corresponding rule intents and one or more rule types in the rule repository; trigger an annotation module to highlight the business rule in a document and to annotate the business rule with at least one of the one or more rule intents and rule types in the rule repository; cluster the one or more rule intents in an agglomerative manner to identify one or more clustering rule intents that co-occur frequently in the rule repository; assemble the one or more clusters into a plurality of clustering techniques, wherein the rule repository is periodically updated with the corresponding rule intent and the rule type to classify sentences obtained from a training data set; and automatically associate the business rules extracted from the text document with a plurality of corresponding knowledge element types and system components to reference, trace and re-use at least one of requirement artifacts and system documentation. 11. The computer implemented system as claimed in claim 6 , wherein the business rule classification system further includes an association module configured to identify associations of the business rule with knowledge element types, system components, and stakeholders based on the at least rule type under which the business rule is classified.

26. A method in accordance with claim 24 wherein: the output communication indicates that the person should be studied.

26. A method in accordance with claim 24 wherein: the output communication indicates that the person should be studied. 27. A method in accordance with claim 26 wherein: the output communication regards at least one of the psychological state of the person represented by the at least one communication originated by the person and an investigation of the psychological state of the person represented by the at least one communication.

1. A method comprising: outputting, by a computing device and for display at a presence-sensitive display, a graphical user interface associated with an application executing at the computing device, the graphical user interface comprising an input field and a graphical keyboard, the graphical keyboard comprising a group of keys, wherein each key in the group of keys is associated with a respective, different region of the presence-sensitive display; receiving, at the computing device, an indication of a gesture to select a sequence of keys that are each included in the group of keys of the graphical keyboard; determining, by the computing device, that the selected sequence of keys corresponds to a character string that is identifiable by a format source, wherein the format source is associated with a syntax, the format source and the syntax being determined based on syntax information associated with the input field; determining, by the computing device and based at least in part on the syntax, that at least one separator character is associated with the character string, wherein the gesture does not indicate a key associated with the at least one separator character, and wherein the syntax comprises a set of rules that define one or more combinations of symbols or characters that are structurally valid in a given context defined as the input field; and in response to determining that the at least one separator character is associated with the character string for the given context, outputting, by the computing device, for display within the input field, the character string and the at least one separator character between at least two characters of the character string.

1. A method comprising: outputting, by a computing device and for display at a presence-sensitive display, a graphical user interface associated with an application executing at the computing device, the graphical user interface comprising an input field and a graphical keyboard, the graphical keyboard comprising a group of keys, wherein each key in the group of keys is associated with a respective, different region of the presence-sensitive display; receiving, at the computing device, an indication of a gesture to select a sequence of keys that are each included in the group of keys of the graphical keyboard; determining, by the computing device, that the selected sequence of keys corresponds to a character string that is identifiable by a format source, wherein the format source is associated with a syntax, the format source and the syntax being determined based on syntax information associated with the input field; determining, by the computing device and based at least in part on the syntax, that at least one separator character is associated with the character string, wherein the gesture does not indicate a key associated with the at least one separator character, and wherein the syntax comprises a set of rules that define one or more combinations of symbols or characters that are structurally valid in a given context defined as the input field; and in response to determining that the at least one separator character is associated with the character string for the given context, outputting, by the computing device, for display within the input field, the character string and the at least one separator character between at least two characters of the character string. 7. The method of claim 1 , wherein the syntax comprises at least one of: a Uniform Resource Locator (URL) syntax, wherein the URL syntax includes a set of separator characters associated with a URL; a date syntax, wherein the date syntax includes a set of separator characters associated with a date; and a time syntax, wherein the time syntax includes a set of separator characters associated with a time of day.

17. A method for processing queries, comprising the computer-implemented steps of: a database server receiving a query that evaluates to a relation, wherein said query comprises: a first one or more clauses; and a model clause, wherein said model clause comprises: a rule that comprises a left-side expression and a right-side expression, wherein said right-side expression includes a window function; and one or more dimension columns that correspond to columns of said relation, wherein said left-side expression references a set of said one or more dimension columns; wherein said window function specifies a set of columns over which said window function is to be evaluated, wherein said set of columns corresponds to columns of said relation; said database server executing said query to generate said relation, wherein said database server executing said query comprises: producing a first set of rows, wherein each row in said first set of rows includes only: said set of columns that is specified by said window function, and said set of said one or more dimension columns that is referenced by said left-side expression; evaluating said window function based on said first set of rows; wherein the steps of the method are performed by one or more computer systems.

17. A method for processing queries, comprising the computer-implemented steps of: a database server receiving a query that evaluates to a relation, wherein said query comprises: a first one or more clauses; and a model clause, wherein said model clause comprises: a rule that comprises a left-side expression and a right-side expression, wherein said right-side expression includes a window function; and one or more dimension columns that correspond to columns of said relation, wherein said left-side expression references a set of said one or more dimension columns; wherein said window function specifies a set of columns over which said window function is to be evaluated, wherein said set of columns corresponds to columns of said relation; said database server executing said query to generate said relation, wherein said database server executing said query comprises: producing a first set of rows, wherein each row in said first set of rows includes only: said set of columns that is specified by said window function, and said set of said one or more dimension columns that is referenced by said left-side expression; evaluating said window function based on said first set of rows; wherein the steps of the method are performed by one or more computer systems. 22. The method of claim 17 , wherein: said window function specifies one or more partition columns by which to partition a second set of rows in said relation into partitions, wherein said second set of rows includes one or more cells that are identified by said left-side expression of said rule; said step of said database server executing said query further comprises: based on said left-side expression, determining said second set of rows in said relation; and based on said one or more partition columns, partitioning said second set of rows into one or more subsets of rows; said step of producing said first set of rows comprises producing said first set of rows based on at least one of said one or more subsets of rows.

1. In history matching the results of computer implemented simulation with reservoir field production data from the reservoir to conform the reservoir simulation with the field production data, a computer implemented method to modify input data regarding the reservoir to more satisfactorily match the reservoir to the field production data based on specified modify instructions regarding simulator input data about the reservoir, the computer implemented method comprising the steps of: converting the modify instructions into a computer recognizable token; parsing the computer recognizable token according to a grammar to form a modify data structure; determining in the computer if the modify data structure identifies a reservoir variable, and if so, finding a pointer in computer memory to the variable; and determining in the computer if the modify data structure identifies an operator, and if so, performing the operation according to the identified operator data to modify the simulator input data.

1. In history matching the results of computer implemented simulation with reservoir field production data from the reservoir to conform the reservoir simulation with the field production data, a computer implemented method to modify input data regarding the reservoir to more satisfactorily match the reservoir to the field production data based on specified modify instructions regarding simulator input data about the reservoir, the computer implemented method comprising the steps of: converting the modify instructions into a computer recognizable token; parsing the computer recognizable token according to a grammar to form a modify data structure; determining in the computer if the modify data structure identifies a reservoir variable, and if so, finding a pointer in computer memory to the variable; and determining in the computer if the modify data structure identifies an operator, and if so, performing the operation according to the identified operator data to modify the simulator input data. 4. The computer implemented method of claim 1 , wherein the step of parsing the computer recognizable token is performed with bison processing of a grammar.

13. The electronic device of claim 11 , wherein the analysis and save module further identifies templates in a callstack for the overriding templates that are modified, the analysis and save module saving the modified portions of each identified template in the callstack.

13. The electronic device of claim 11 , wherein the analysis and save module further identifies templates in a callstack for the overriding templates that are modified, the analysis and save module saving the modified portions of each identified template in the callstack. 14. The electronic device of claim 13 , wherein the analysis and save module incorporates the modified portions of each identified template in the callstack into XML data of the web parts that are edited.

3. The system of claim 1 , wherein the learning component generates a quality value for each candidate process model in the set of candidate process models to facilitate selection of the particular process model from the set of candidate process models.

3. The system of claim 1 , wherein the learning component generates a quality value for each candidate process model in the set of candidate process models to facilitate selection of the particular process model from the set of candidate process models. 5. The system of claim 3 , wherein the learning component further generates a diversity value associated with uniqueness for each candidate process model in the set of candidate process models.

6. An apparatus comprising: means for receiving input data, the input data being data for conversion from a phonetic representation or speech to written text characters of one or more words of a language, the input data having a plurality of data pieces; means for calculating, via an iterative process, a vector for the input data in a textual format of the language, the iterative process including starting with a first data piece of the input data converted to a selected textual format to form a current vector of the input data and iteratively updating the current vector with a next data piece of the input data using elements of the current vector until all the data pieces are converted into the textual format; means for dividing a plurality of documents into a first subset similar to the input data and a second subset dissimilar to the input data based on the vector for the input data, the plurality of documents having text being written in the language; means for determining a frequency text in the first subset; and means for converting the input data to a representation of one or more written text characters of the language based on the frequency of the text in the first subset.

6. An apparatus comprising: means for receiving input data, the input data being data for conversion from a phonetic representation or speech to written text characters of one or more words of a language, the input data having a plurality of data pieces; means for calculating, via an iterative process, a vector for the input data in a textual format of the language, the iterative process including starting with a first data piece of the input data converted to a selected textual format to form a current vector of the input data and iteratively updating the current vector with a next data piece of the input data using elements of the current vector until all the data pieces are converted into the textual format; means for dividing a plurality of documents into a first subset similar to the input data and a second subset dissimilar to the input data based on the vector for the input data, the plurality of documents having text being written in the language; means for determining a frequency text in the first subset; and means for converting the input data to a representation of one or more written text characters of the language based on the frequency of the text in the first subset. 10. The apparatus of claim 6 , wherein the input data comprises Kana characters.

8. In a computing environment, a system comprising: at least one processor; a memory communicatively connect with the at least one processor; a plurality of reusable software components programmed in a dynamically-typed programming language; design surface by which programming code is developed via placement of icons, the icons comprising graphical representations of the reusable components of the programming code; sets of metadata, each set of metadata comprising explicit identification of a data type corresponding to a component of the plurality of reusable components a development environment configured to validate usage of a first reusable software component based on a data type indentified in a corresponding first set of metadata, in response to placement of a first icon corresponding to a first reusable software component on the design surface in connection with a second icon representing a second reusable software component a runtime system configured to run the programming code and use the first set Of metadata to validate execution of the programming code at runtime by performing enhanced type matching during execution, including insertion executable code into the selected programming language component that converts one data type to an appropriate type for input or output; the development environment operative to provide program metadata or executable code, or both program metadata and executable code for the programming code, to the runtime system; and the runtime system comprising an interpreter that interprets the program metadata and an engine that runs the interpreter or the executable code.

8. In a computing environment, a system comprising: at least one processor; a memory communicatively connect with the at least one processor; a plurality of reusable software components programmed in a dynamically-typed programming language; design surface by which programming code is developed via placement of icons, the icons comprising graphical representations of the reusable components of the programming code; sets of metadata, each set of metadata comprising explicit identification of a data type corresponding to a component of the plurality of reusable components a development environment configured to validate usage of a first reusable software component based on a data type indentified in a corresponding first set of metadata, in response to placement of a first icon corresponding to a first reusable software component on the design surface in connection with a second icon representing a second reusable software component a runtime system configured to run the programming code and use the first set Of metadata to validate execution of the programming code at runtime by performing enhanced type matching during execution, including insertion executable code into the selected programming language component that converts one data type to an appropriate type for input or output; the development environment operative to provide program metadata or executable code, or both program metadata and executable code for the programming code, to the runtime system; and the runtime system comprising an interpreter that interprets the program metadata and an engine that runs the interpreter or the executable code. 12. The system of claim 8 wherein the first set of metadata comprises at least some data defined according to an extensible markup language (XML) schema.

1. A method for deriving a process-based specification for a system, comprising: deriving a trace-based specification from a non-empty set of traces by a processor, wherein a trace is a sequence of actions expressed as strings representing a history of an execution of a process; mathematically inferring the process-based specification from the trace-based specification, wherein mathematically inferring includes applying Laws of Concurrency in reverse to a set of system traces to determine the process-based specification, wherein the process-based specification is mathematically equivalent to the trace-based specification, and whereby the Laws of Concurrency are algebraic laws that (a) allow at least one process to be manipulated and analyzed, (b) permit formal reasoning about equivalences between processes, and (c) determine traces from the at least one process; generating the process-based specification using an inference engine, wherein the inference engine iteratively applies a set of rules to a set of data representing a problem to determine a solution to the problem by logical manipulation and analysis of the set of data; and analyzing the process-based specification to examine possible implementations of the process-based specification in different configurations, whereby analyzing includes identifying at least one equivalent alternative process-based specification and characterizing differences between the process-based specification and the at least one alternative process-based specification, wherein differences include number of processes, deterministic behavior, and competition for resources.

1. A method for deriving a process-based specification for a system, comprising: deriving a trace-based specification from a non-empty set of traces by a processor, wherein a trace is a sequence of actions expressed as strings representing a history of an execution of a process; mathematically inferring the process-based specification from the trace-based specification, wherein mathematically inferring includes applying Laws of Concurrency in reverse to a set of system traces to determine the process-based specification, wherein the process-based specification is mathematically equivalent to the trace-based specification, and whereby the Laws of Concurrency are algebraic laws that (a) allow at least one process to be manipulated and analyzed, (b) permit formal reasoning about equivalences between processes, and (c) determine traces from the at least one process; generating the process-based specification using an inference engine, wherein the inference engine iteratively applies a set of rules to a set of data representing a problem to determine a solution to the problem by logical manipulation and analysis of the set of data; and analyzing the process-based specification to examine possible implementations of the process-based specification in different configurations, whereby analyzing includes identifying at least one equivalent alternative process-based specification and characterizing differences between the process-based specification and the at least one alternative process-based specification, wherein differences include number of processes, deterministic behavior, and competition for resources. 9. The method of claim 1 , wherein the various possible implementations of the process-based specification are based on transformations of the process-based specification by applying the Law of Concurrency to derive various implementations.

72. A method of identifying a television signal received from either a television receiver or a video recorder for determining audience viewing habits comprising the steps of: detecting predetermined operational modes of the audience member's television receiver and the video recorder; detecting the occurence of a first event in one of the operational modes; detecting the occurence of a second event in the signal to be identified; extracting a signature from a single frame of the video signal to be identified after the occurence of the second event; and storing the extracted signature, the time of the signature extraction and the detected operational mode.

72. A method of identifying a television signal received from either a television receiver or a video recorder for determining audience viewing habits comprising the steps of: detecting predetermined operational modes of the audience member's television receiver and the video recorder; detecting the occurence of a first event in one of the operational modes; detecting the occurence of a second event in the signal to be identified; extracting a signature from a single frame of the video signal to be identified after the occurence of the second event; and storing the extracted signature, the time of the signature extraction and the detected operational mode. 76. The method recited in claim 72 wherein said second event is a scene change from one video scene to another video scene.

8. The method of claim 2 further comprising the step of optimizing the plurality of components.

8. The method of claim 2 further comprising the step of optimizing the plurality of components. 10. The method of claim 8 , wherein the step of optimizing includes validation for component duplication.

1. A computer-implemented method comprising: (A) generating a first partial audio stream representing first speech of a speaker; (B) associating with the first partial audio stream a first time relative to a reference point in a dictation stream, of which the first partial audio stream is a part; (C) generating a second partial audio stream representing second speech of the speaker; (D) associating with the second partial audio stream a second time relative to the reference point in the dictation stream, of which the second partial audio stream is a part, wherein the first and second partial audio streams are not contiguous in time relative to the reference point; and (E) at a consumer: (1) receiving the first partial audio stream; (2) writing the first partial audio stream into an effective dictation stream at a position based on the first time; (3) receiving the second partial audio stream; (4) writing the second partial audio stream into the effective dictation stream at a position based on the second time; and (5) consuming at least part of the effective dictation to produce output before completion of (E)(4).

1. A computer-implemented method comprising: (A) generating a first partial audio stream representing first speech of a speaker; (B) associating with the first partial audio stream a first time relative to a reference point in a dictation stream, of which the first partial audio stream is a part; (C) generating a second partial audio stream representing second speech of the speaker; (D) associating with the second partial audio stream a second time relative to the reference point in the dictation stream, of which the second partial audio stream is a part, wherein the first and second partial audio streams are not contiguous in time relative to the reference point; and (E) at a consumer: (1) receiving the first partial audio stream; (2) writing the first partial audio stream into an effective dictation stream at a position based on the first time; (3) receiving the second partial audio stream; (4) writing the second partial audio stream into the effective dictation stream at a position based on the second time; and (5) consuming at least part of the effective dictation to produce output before completion of (E)(4). 13. The method of claim 1 , further comprising: (F) identifying contextual information associated with the first partial audio stream; (G) associating the first time of the first partial audio stream with the contextual information; and (H) at the consumer, receiving the contextual information in association with the first time of the first partial audio stream.